Author
Shahana Ahmed
Bio: Shahana Ahmed is an academic researcher from University of Cambridge. The author has contributed to research in topics: Breast cancer & Genome-wide association study. The author has an hindex of 37, co-authored 57 publications receiving 7936 citations.
Papers
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University of Cambridge1, National Institutes of Health2, University of Southern California3, International Agency for Research on Cancer4, Academia Sinica5, Princess Anne Hospital6, St Mary's Hospital7, University of London8, The Breast Cancer Research Foundation9, Wellcome Trust Sanger Institute10, Peter MacCallum Cancer Centre11, QIMR Berghofer Medical Research Institute12, University of Copenhagen13, Curie Institute14, Nofer Institute of Occupational Medicine15, University of Helsinki16, Seoul National University17, University of Ulsan18, Harvard University19, Karolinska Institutet20, Agency for Science, Technology and Research21, Hannover Medical School22, Leiden University23, Erasmus University Rotterdam24, University of Minnesota25, University of Sheffield26, Mayo Clinic27, VU University Amsterdam28, Carlos III Health Institute29, University of Melbourne30, Cancer Council New South Wales31, University of Otago32, Cancer Council Victoria33, Bosch34, University of Tübingen35, German Cancer Research Center36, University of Eastern Finland37
TL;DR: To identify further susceptibility alleles, a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls was conducted, followed by a third stage in which 30 single nucleotide polymorphisms were tested for confirmation.
Abstract: Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate risks. To identify further susceptibility alleles, we conducted a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls, followed by a third stage in which 30 single nucleotide polymorphisms (SNPs) were tested for confirmation in 21,860 cases and 22,578 controls from 22 studies. We used 227,876 SNPs that were estimated to correlate with 77% of known common SNPs in Europeans at r2.0.5. SNPs in five novel independent loci exhibited strong and consistent evidence of association with breast cancer (P,1027). Four of these contain plausible causative genes (FGFR2, TNRC9, MAP3K1 and LSP1). At the second stage, 1,792 SNPs were significant at the P,0.05 level compared with an estimated 1,343 that would be expected by chance, indicating that many additional common susceptibility alleles may be identifiable by this approach.
2,288 citations
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TL;DR: Previously identified breast cancer susceptibility loci were found to show larger effect sizes in this study of familial breast cancer cases than in previous population-based studies, consistent with polygenic susceptibility to the disease.
Abstract: Breast cancer is the most common cancer in women in developed countries. To identify common breast cancer susceptibility alleles, we conducted a genome-wide association study in which 582,886 SNPs were genotyped in 3,659 cases with a family history of the disease and 4,897 controls. Promising associations were evaluated in a second stage, comprising 12,576 cases and 12,223 controls. We identified five new susceptibility loci, on chromosomes 9, 10 and 11 (P = 4.6 x 10(-7) to P = 3.2 x 10(-15)). We also identified SNPs in the 6q25.1 (rs3757318, P = 2.9 x 10(-6)), 8q24 (rs1562430, P = 5.8 x 10(-7)) and LSP1 (rs909116, P = 7.3 x 10(-7)) regions that showed more significant association with risk than those reported previously. Previously identified breast cancer susceptibility loci were also found to show larger effect sizes in this study of familial breast cancer cases than in previous population-based studies, consistent with polygenic susceptibility to the disease.
703 citations
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Rosalind A. Eeles1, Ali Amin Al Olama2, Sara Benlloch2, Edward J. Saunders +153 more•Institutions (46)
TL;DR: In this paper, a custom Illumina array (iCOGS) was used to genotype 211,155 SNPs in blood DNA from 25,074 prostate cancer cases and 24,272 controls from the international PRACTICAL Consortium.
Abstract: Prostate cancer is the most frequently diagnosed cancer in males in developed countries. To identify common prostate cancer susceptibility alleles, we genotyped 211,155 SNPs on a custom Illumina array (iCOGS) in blood DNA from 25,074 prostate cancer cases and 24,272 controls from the international PRACTICAL Consortium. Twenty-three new prostate cancer susceptibility loci were identified at genome-wide significance (P < 5 × 10(-8)). More than 70 prostate cancer susceptibility loci, explaining ∼30% of the familial risk for this disease, have now been identified. On the basis of combined risks conferred by the new and previously known risk loci, the top 1% of the risk distribution has a 4.7-fold higher risk than the average of the population being profiled. These results will facilitate population risk stratification for clinical studies.
523 citations
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Stig E. Bojesen1, Stig E. Bojesen2, Karen A. Pooley3, Sharon E. Johnatty4 +452 more•Institutions (129)
TL;DR: Using the Illumina custom genotyping array iCOGs, SNPs at the TERT locus in breast, ovarian and BRCA1 mutation carrier cancer cases and controls and leukocyte telomere measurements are analyzed to find associations cluster into three independent peaks.
Abstract: TERT-locus SNPs and leukocyte telomere measures are reportedly associated with risks of multiple cancers. Using the Illumina custom genotyping array iCOG, we analyzed similar to 480 SNPs at the TERT locus in breast (n = 103,991), ovarian (n = 39,774) and BRCA1 mutation carrier (n = 11,705) cancer cases and controls. Leukocyte telomere measurements were also available for 53,724 participants. Most associations cluster into three independent peaks. The minor allele at the peak 1 SNP rs2736108 associates with longer telomeres (P = 5.8 x 10(-7)), lower risks for estrogen receptor (ER)-negative (P = 1.0 x 10(-8)) and BRCA1 mutation carrier (P = 1.1 x 10(-5)) breast cancers and altered promoter assay signal. The minor allele at the peak 2 SNP rs7705526 associates with longer telomeres (P = 2.3 x 10(-14)), higher risk of low-malignant-potential ovarian cancer (P = 1.3 x 10(-15)) and greater promoter activity. The minor alleles at the peak 3 SNPs rs10069690 and rs2242652 increase ER-negative (P = 1.2 x 10(-12)) and BRCA1 mutation carrier (P = 1.6 x 10-14) breast and invasive ovarian (P = 1.3 x 10(-11)) cancer risks but not via altered telomere length. The cancer risk alleles of rs2242652 and rs10069690, respectively, increase silencing and generate a truncated TERT splice variant.
522 citations
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University of Cambridge1, National Institutes of Health2, Princess Anne Hospital3, St Mary's Hospital4, Wellcome Trust Sanger Institute5, Science Applications International Corporation6, Fred Hutchinson Cancer Research Center7, Baylor College of Medicine8, University of Hawaii at Manoa9, University of Utah10, Marshfield Clinic11, American Cancer Society12, University of Copenhagen13, Hannover Medical School14, Russian Academy15, Seoul National University16, Leiden University17, Erasmus University Rotterdam18, Curie Institute19, Nofer Institute of Occupational Medicine20, University of Helsinki21, University of Melbourne22, QIMR Berghofer Medical Research Institute23, Netherlands Cancer Institute24, Carlos III Health Institute25, University of Cologne26, Heidelberg University27, German Cancer Research Center28, Technische Universität München29, Bosch30, University of Tübingen31, University of Ulm32, Karolinska Institutet33, University of Eastern Finland34, Mayo Clinic35, Cancer Council Victoria36, Harvard University37, Norwegian University of Science and Technology38, University of Minnesota39, Agency for Science, Technology and Research40, University of Sheffield41, Academia Sinica42, China Medical University (Taiwan)43, National Defense Medical Center44, University of California, Irvine45, University of Toronto46, Cancer Research UK47
TL;DR: Strong evidence is found for additional susceptibility loci on 3p and 17q and potential causative genes include SLC4A7 and NEK10 on3p and COX11 on 17q.
Abstract: Genome-wide association studies (GWAS) have identified seven breast cancer susceptibility loci, but these explain only a small fraction of the familial risk of the disease. Five of these loci were identified through a two-stage GWAS involving 390 familial cases and 364 controls in the first stage, and 3,990 cases and 3,916 controls in the second stage. To identify additional loci, we tested over 800 promising associations from this GWAS in a further two stages involving 37,012 cases and 40,069 controls from 33 studies in the CGEMS collaboration and Breast Cancer Association Consortium. We found strong evidence for additional susceptibility loci on 3p (rs4973768: per-allele OR = 1.11, 95% CI = 1.08-1.13, P = 4.1 x 10(-23)) and 17q (rs6504950: per-allele OR = 0.95, 95% CI = 0.92-0.97, P = 1.4 x 10(-8)). Potential causative genes include SLC4A7 and NEK10 on 3p and COX11 on 17q.
480 citations
Cited by
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National Institutes of Health1, University of Chicago2, Duke University3, Harvard University4, University of Oxford5, GlaxoSmithKline6, Johns Hopkins University7, Yale University8, deCODE genetics9, Princeton University10, Howard Hughes Medical Institute11, Washington University in St. Louis12, University of California, Berkeley13, Stanford University14, University of Michigan15, Cornell University16, University of Washington17, University of Queensland18, Vanderbilt University19, North Carolina State University20, QIMR Berghofer Medical Research Institute21
TL;DR: This paper examined potential sources of missing heritability and proposed research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
Abstract: Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
7,797 citations
01 Feb 2015
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.
4,409 citations
01 Jan 2000
3,536 citations
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University of Oxford1, Wellcome Trust Centre for Human Genetics2, University of Michigan3, Fred Hutchinson Cancer Research Center4, Duke University5, University of Ottawa6, Tufts University7, Foundation for Research & Technology – Hellas8, Broad Institute9, Harvard University10, Boston Children's Hospital11
TL;DR: This Review highlights the knowledge gained, defines areas of emerging consensus, and describes the challenges that remain as researchers seek to obtain more complete descriptions of the susceptibility architecture of biomedical traits of interest and to translate the information gathered into improvements in clinical management.
Abstract: The past year has witnessed substantial advances in understanding the genetic basis of many common phenotypes of biomedical importance. These advances have been the result of systematic, well-powered, genome-wide surveys exploring the relationships between common sequence variation and disease predisposition. This approach has revealed over 50 disease-susceptibility loci and has provided insights into the allelic architecture of multifactorial traits. At the same time, much has been learned about the successful prosecution of association studies on such a scale. This Review highlights the knowledge gained, defines areas of emerging consensus, and describes the challenges that remain as researchers seek to obtain more complete descriptions of the susceptibility architecture of biomedical traits of interest and to translate the information gathered into improvements in clinical management.
2,908 citations
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TL;DR: In this paper, the coding exons of the family of 518 protein kinases were sequenced in 210 cancers of diverse histological types to explore the nature of the information that will be derived from cancer genome sequencing.
Abstract: AACR Centennial Conference: Translational Cancer Medicine-- Nov 4-8, 2007; Singapore
PL02-05
All cancers are due to abnormalities in DNA. The availability of the human genome sequence has led to the proposal that resequencing of cancer genomes will reveal the full complement of somatic mutations and hence all the cancer genes. To explore the nature of the information that will be derived from cancer genome sequencing we have sequenced the coding exons of the family of 518 protein kinases, ~1.3Mb DNA per cancer sample, in 210 cancers of diverse histological types. Despite the screen being directed toward the coding regions of a gene family that has previously been strongly implicated in oncogenesis, the results indicate that the majority of somatic mutations detected are “passengers”. There is considerable variation in the number and pattern of these mutations between individual cancers, indicating substantial diversity of processes of molecular evolution between cancers. The imprints of exogenous mutagenic exposures, mutagenic treatment regimes and DNA repair defects can all be seen in the distinctive mutational signatures of individual cancers. This systematic mutation screen and others have previously yielded a number of cancer genes that are frequently mutated in one or more cancer types and which are now anticancer drug targets (for example BRAF , PIK3CA , and EGFR ). However, detailed analyses of the data from our screen additionally suggest that there exist a large number of additional “driver” mutations which are distributed across a substantial number of genes. It therefore appears that cells may be able to utilise mutations in a large repertoire of potential cancer genes to acquire the neoplastic phenotype. However, many of these genes are employed only infrequently. These findings may have implications for future anticancer drug development.
2,737 citations