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Chris Schroen

Bio: Chris Schroen is an academic researcher from University of Melbourne. The author has contributed to research in topics: Genome-wide association study & Cancer. The author has an hindex of 2, co-authored 2 publications receiving 2261 citations.

Papers
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Journal ArticleDOI
Douglas F. Easton1, Karen A. Pooley1, Alison M. Dunning1, Paul D.P. Pharoah1, Deborah J. Thompson1, Dennis G. Ballinger, Jeffery P. Struewing2, Jonathan J. Morrison1, Helen I. Field1, Robert Luben1, Nicholas J. Wareham1, Shahana Ahmed1, Catherine S. Healey1, Richard Bowman, Kerstin B. Meyer1, Christopher A. Haiman3, Laurence K. Kolonel, Brian E. Henderson3, Loic Le Marchand, Paul Brennan4, Suleeporn Sangrajrang, Valerie Gaborieau4, Fabrice Odefrey4, Chen-Yang Shen5, Pei-Ei Wu5, Hui-Chun Wang5, Diana Eccles6, D. Gareth Evans7, Julian Peto8, Olivia Fletcher9, Nichola Johnson9, Sheila Seal, Michael R. Stratton10, Nazneen Rahman, Georgia Chenevix-Trench11, Georgia Chenevix-Trench12, Stig E. Bojesen13, Børge G. Nordestgaard13, C K Axelsson13, Montserrat Garcia-Closas2, Louise A. Brinton2, Stephen J. Chanock2, Jolanta Lissowska14, Beata Peplonska15, Heli Nevanlinna16, Rainer Fagerholm16, H Eerola16, Daehee Kang17, Keun-Young Yoo17, Dong-Young Noh17, Sei Hyun Ahn18, David J. Hunter19, Susan E. Hankinson19, David G. Cox19, Per Hall20, Sara Wedrén20, Jianjun Liu21, Yen-Ling Low21, Natalia Bogdanova22, Peter Schu¨rmann22, Do¨rk Do¨rk22, Rob A. E. M. Tollenaar23, Catharina E. Jacobi23, Peter Devilee23, Jan G. M. Klijn24, Alice J. Sigurdson2, Michele M. Doody2, Bruce H. Alexander25, Jinghui Zhang2, Angela Cox26, Ian W. Brock26, Gordon MacPherson26, Malcolm W.R. Reed26, Fergus J. Couch27, Ellen L. Goode27, Janet E. Olson27, Hanne Meijers-Heijboer28, Hanne Meijers-Heijboer24, Ans M.W. van den Ouweland24, André G. Uitterlinden24, Fernando Rivadeneira24, Roger L. Milne29, Gloria Ribas29, Anna González-Neira29, Javier Benitez29, John L. Hopper30, Margaret R. E. McCredie31, Margaret R. E. McCredie32, Margaret R. E. McCredie12, Melissa C. Southey12, Melissa C. Southey30, Graham G. Giles33, Chris Schroen30, Christina Justenhoven34, Christina Justenhoven35, Hiltrud Brauch35, Hiltrud Brauch34, Ute Hamann36, Yon-Dschun Ko, Amanda B. Spurdle11, Jonathan Beesley11, Xiaoqing Chen11, _ kConFab37, Arto Mannermaa37, Veli-Matti Kosma37, Vesa Kataja37, Jaana M. Hartikainen37, Nicholas E. Day1, David Cox, Bruce A.J. Ponder1 
28 Jun 2007-Nature
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

Journal ArticleDOI
TL;DR: There are strong familial correlations in postmenopausal SHBG, IGF-I, and to a lesser extent T, which are consistent with a genetic etiology and substantial nongenetic familial factors.
Abstract: Background: Serum concentrations of some hormones are risk factors for certain cancers, but little is known about their familial associations especially for females. Methods: We measured serum concentrations of estradiol (E2), testosterone (T), SHBG, prolactin, and IGF-I for 645 Australian female postmenopausal twins and their sisters [182 monozygotic (MZ) and 107 dizygotic (DZ) pairs and 67 nontwin sisters] using well-established immunoassays. After suitable transformation and adjusting for age, body mass index (BMI), and time since menopause, familial correlations and proportions of variance attributed to genetic (h2) and nongenetic factors common to sisterships (c2) were estimated under the classic twin multivariate normal model using FISHER. Results: For all serum concentrations except prolactin, MZ, DZ, and sister pairs were correlated (P < 0.001). MZ correlations were in the range 0.5–0.7, and for all serum concentrations, there were no differences between DZ and sister correlations. MZ correlations...

24 citations


Cited by
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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

Journal Article
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

Journal ArticleDOI
TL;DR: A variance component approach implemented in publicly available software, EMMA eXpedited (EMMAX), that reduces the computational time for analyzing large GWAS data sets from years to hours is reported.
Abstract: Although genome-wide association studies (GWASs) have identified numerous loci associated with complex traits, imprecise modeling of the genetic relatedness within study samples may cause substantial inflation of test statistics and possibly spurious associations. Variance component approaches, such as efficient mixed-model association (EMMA), can correct for a wide range of sample structures by explicitly accounting for pairwise relatedness between individuals, using high-density markers to model the phenotype distribution; but such approaches are computationally impractical. We report here a variance component approach implemented in publicly available software, EMMA eXpedited (EMMAX), that reduces the computational time for analyzing large GWAS data sets from years to hours. We apply this method to two human GWAS data sets, performing association analysis for ten quantitative traits from the Northern Finland Birth Cohort and seven common diseases from the Wellcome Trust Case Control Consortium. We find that EMMAX outperforms both principal component analysis and genomic control in correcting for sample structure.

2,316 citations

Journal ArticleDOI
TL;DR: There is now substantial evidence for the importance of FGF signalling in the pathogenesis of diverse tumour types, and clinical reagents that specifically target the FGFs or FGF receptors are being developed.
Abstract: Fibroblast growth factors (FGFs) and their receptors control a wide range of biological functions, regulating cellular proliferation, survival, migration and differentiation. Although targeting FGF signalling as a cancer therapeutic target has lagged behind that of other receptor tyrosine kinases, there is now substantial evidence for the importance of FGF signalling in the pathogenesis of diverse tumour types, and clinical reagents that specifically target the FGFs or FGF receptors are being developed. Although FGF signalling can drive tumorigenesis, in different contexts FGF signalling can mediate tumour protective functions; the identification of the mechanisms that underlie these differential effects will be important to understand how FGF signalling can be most appropriately therapeutically targeted.

2,211 citations