ORCID Profile
0000-0002-2272-1277
Current Organisation
The University of Edinburgh
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Publisher: Cold Spring Harbor Laboratory
Date: 19-06-2020
DOI: 10.1101/2020.06.16.146803
Abstract: We report a meta-analysis of breast, prostate, ovarian, and endometrial cancer genome-wide association data (effective s le size: 237,483 cases/317,006 controls). This identified 465 independent lead variants ( P ×10 −8 ) across 192 genomic regions. Four lead variants were Mb from previously identified risk loci for the four cancers and an additional 23 lead variant-cancer associations were novel for one of the cancers. Bayesian models supported pleiotropic effects involving at least two cancers at 222/465 lead variants in 118/192 regions. Gene-level association analysis identified 13 shared susceptibility genes ( P .6×10 −6 ) in 13 regions not previously implicated in any of the four cancers and not uncovered by our variant-level meta-analysis. Several lead variants had opposite effects across cancers, including a cluster of such variants in the TP53 pathway. Fifty-four lead variants were associated with blood cell traits and suggested genetic overlaps with clonal hematopoiesis. Our study highlights the remarkable pervasiveness of pleiotropy across hormone-related cancers, further illuminating their shared genetic and mechanistic origins at variant- and gene-level resolution.
Publisher: Cold Spring Harbor Laboratory
Date: 02-05-2020
DOI: 10.1101/2020.04.29.20084095
Abstract: Accumulating evidence suggests a relationship between endometrial cancer and epithelial ovarian cancer. For ex le, endometrial cancer and epithelial ovarian cancer share epidemiological risk factors and molecular features observed across histotypes are held in common (e.g. serous, endometrioid and clear cell). Independent genome-wide association studies (GWAS) for endometrial cancer and epithelial ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. Using GWAS summary statistics, we explored the shared genetic etiology between endometrial cancer and epithelial ovarian cancer. Genetic correlation analysis using LD Score regression revealed significant genetic correlation between the two cancers ( r G = 0.43, P = 2.66 × 10 −5 ). To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e. inverse-variance meta-analysis, co-localization, and M-values), and performed analyses by stratified by subtype. We found seven loci associated with risk for both cancers (P Bonferroni 2.4 × 10 −9 ). In addition, four novel regions at 7p22.2, 7q22.1, 9p12 and 11q13.3 were identified at a sub-genome wide threshold (P 5 × 10 −7 ). Integration with promoter-associated HiChIP chromatin loops from immortalized endometrium and epithelial ovarian cell lines, and expression quantitative trait loci (eQTL) data highlighted candidate target genes for further investigation.
Publisher: Springer Science and Business Media LLC
Date: 24-06-2020
Publisher: Springer Science and Business Media LLC
Date: 27-03-2017
DOI: 10.1038/NG.3826
Publisher: Cold Spring Harbor Laboratory
Date: 08-12-2019
DOI: 10.1101/868679
Abstract: Cancers arise through the acquisition of oncogenic mutations and grow through clonal expansion 1, 2 . Here we reveal that most mutagenic DNA lesions are not resolved as mutations within a single cell-cycle. Instead, DNA lesions segregate unrepaired into daughter cells for multiple cell generations, resulting in the chromosome-scale phasing of subsequent mutations. We characterise this process in mutagen-induced mouse liver tumours and show that DNA replication across persisting lesions can generate multiple alternative alleles in successive cell isions, thereby increasing both multi-allelic and combinatorial genetic ersity. The phasing of lesions enables the accurate measurement of strand biased repair processes, the quantification of oncogenic selection, and the fine mapping of sister chromatid exchange events. Finally, we demonstrate that lesion segregation is a unifying property of exogenous mutagens, including UV light and chemotherapy agents in human cells and tumours, which has profound implications for the evolution and adaptation of cancer genomes.
Publisher: Springer Science and Business Media LLC
Date: 20-03-2018
Publisher: Springer Science and Business Media LLC
Date: 17-12-2015
DOI: 10.1038/NCOMMS10257
Abstract: Nature Communications 6, Article number: 7756 (2015) Published 4 August 2015 Updated 17 December 2015 In the Results section and in the legend of Table 1 of this Article, the company deCODE genetics, Inc. is incorrectly referred to as ‘Diabetes Epidemiology: collaborative analysis of Diagnostic criteria in Europe’.
Publisher: Springer Science and Business Media LLC
Date: 04-08-2015
DOI: 10.1038/NCOMMS8756
Abstract: More than 100 loci have been identified for age at menarche by genome-wide association studies however, collectively these explain only ∼3% of the trait variance. Here we test two overlooked sources of variation in 192,974 European ancestry women: low-frequency protein-coding variants and X-chromosome variants. Five missense/nonsense variants (in ALMS1 / LAMB2 / TNRC6A/TACR3/PRKAG1 ) are associated with age at menarche (minor allele frequencies 0.08–4.6% effect sizes 0.08–1.25 years per allele P × 10 −8 ). In addition, we identify common X-chromosome loci at IGSF1 (rs762080, P =9.4 × 10 −13 ) and FAAH2 (rs5914101, P =4.9 × 10 −10 ). Highlighted genes implicate cellular energy homeostasis, post-transcriptional gene silencing and fatty-acid amide signalling. A frequently reported mutation in TACR3 for idiopathic hypogonatrophic hypogonadism (p.W275X) is associated with 1.25-year-later menarche ( P =2.8 × 10 −11 ), illustrating the utility of population studies to estimate the penetrance of reportedly pathogenic mutations. Collectively, these novel variants explain ∼0.5% variance, indicating that these overlooked sources of variation do not substantially explain the ‘missing heritability’ of this complex trait.
Publisher: Springer Science and Business Media LLC
Date: 18-02-2019
Publisher: American Association for Cancer Research (AACR)
Date: 2021
DOI: 10.1158/1055-9965.EPI-20-0739
Abstract: Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers. Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data. Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). We found seven loci associated with risk for both cancers (PBonferroni & 2.4 × 10−9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P & 5 × 10−7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation. Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis. Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger s le sets are required to confirm our findings.
Publisher: Springer Science and Business Media LLC
Date: 22-12-2017
Publisher: Springer Science and Business Media LLC
Date: 02-2017
DOI: 10.1038/NATURE21039
Publisher: Springer Science and Business Media LLC
Date: 03-06-2019
DOI: 10.1038/S41588-019-0447-2
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Publisher: Springer Science and Business Media LLC
Date: 28-09-2015
DOI: 10.1038/NG.3412
Publisher: American Association for Cancer Research (AACR)
Date: 03-2016
DOI: 10.1158/1055-9965.EPI-15-0240
Abstract: Background: While numerous susceptibility loci for epithelial ovarian cancer (EOC) have been identified, few associations have been reported with overall survival. In the absence of common prognostic genetic markers, we hypothesize that rare coding variants may be associated with overall EOC survival and assessed their contribution in two exome-based genotyping projects of the Ovarian Cancer Association Consortium (OCAC). Methods: The primary patient set (Set 1) included 14 independent EOC studies (4,293 patients) and 227,892 variants, and a secondary patient set (Set 2) included six additional EOC studies (1,744 patients) and 114,620 variants. Because power to detect rare variants in idually is reduced, gene-level tests were conducted. Sets were analyzed separately at in idual variants and by gene, and then combined with meta-analyses (73,203 variants and 13,163 genes overlapped). Results: No in idual variant reached genome-wide statistical significance. A SNP previously implicated to be associated with EOC risk and, to a lesser extent, survival, rs8170, showed the strongest evidence of association with survival and similar effect size estimates across sets (Pmeta = 1.1E−6, HRSet1 = 1.17, HRSet2 = 1.14). Rare variants in ATG2B, an autophagy gene important for apoptosis, were significantly associated with survival after multiple testing correction (Pmeta = 1.1E−6 Pcorrected = 0.01). Conclusions: Common variant rs8170 and rare variants in ATG2B may be associated with EOC overall survival, although further study is needed. Impact: This study represents the first exome-wide association study of EOC survival to include rare variant analyses, and suggests that complementary single variant and gene-level analyses in large studies are needed to identify rare variants that warrant follow-up study. Cancer Epidemiol Biomarkers Prev 25(3) 446–54. ©2016 AACR.
Publisher: American Association for Cancer Research (AACR)
Date: 15-11-2019
DOI: 10.1158/0008-5472.CAN-19-0037
Abstract: This study provides a useful model for MITF-low melanomas and MITF-independent cell populations that can be used to study the mechanisms that drive these tumors as well as identify potential therapeutic options.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Ailith Ewing.