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16 results on '"Dunning, AM"'

1. A Common Variant at the 14q32 Endometrial Cancer Risk Locus Activates AKT1 through YY1 Binding

Author

Painter, JN, Kaufmann, S, O'Mara, TA, Hillman, KM, Sivakumaran, H, Darabi, H, Cheng, TH, Pearson, J, Kazakoff, S, Waddell, N, Hoivik, EA, Goode, EL, Scott, RJ, Tomlinson, I, Dunning, AM, Easton, DF, French, JD, Salvesen, HB, Pollock, PM, Thompson, DJ, Spurdle, AB, Edwards, SL, Dunning, Alison [0000-0001-6651-7166], Easton, Douglas [0000-0003-2444-3247], Thompson, Deborah [0000-0003-1465-5799], and Apollo - University of Cambridge Repository

Subjects
Chromosomes, Human, Pair 14, Genotype, Polymorphism, Single Nucleotide, Article, Endometrial Neoplasms, Phosphatidylinositol 3-Kinases, Genetic Loci, Risk Factors, Uterine Neoplasms, Genetics, Humans, Genetics(clinical), Female, Genetic Predisposition to Disease, Proto-Oncogene Proteins c-akt, YY1 Transcription Factor, Genome-Wide Association Study, Protein Binding, Signal Transduction
Abstract

A recent meta-analysis of multiple genome-wide association and follow-up endometrial cancer case-control datasets identified a novel genetic risk locus for this disease at chromosome 14q32.33. To prioritize the functional SNP(s) and target gene(s) at this locus, we employed an in silico fine-mapping approach using genotyped and imputed SNP data for 6,608 endometrial cancer cases and 37,925 controls of European ancestry. Association and functional analyses provide evidence that the best candidate causal SNP is rs2494737. Multiple experimental analyses show that SNP rs2494737 maps to a silencer element located within AKT1, a member of the PI3K/AKT/MTOR intracellular signaling pathway activated in endometrial tumors. The rs2494737 risk A allele creates a YY1 transcription factor-binding site and abrogates the silencer activity in luciferase assays, an effect mimicked by transfection of YY1 siRNA. Our findings suggest YY1 is a positive regulator of AKT1, mediating the stimulatory effects of rs2494737 increasing endometrial cancer risk. Identification of an endometrial cancer risk allele within a member of the PI3K/AKT signaling pathway, more commonly activated in tumors by somatic alterations, raises the possibility that well tolerated inhibitors targeting this pathway could be candidates for evaluation as chemopreventive agents in individuals at high risk of developing endometrial cancer.

Published
2016

2. Co-observation of germline pathogenic variants in breast cancer predisposition genes: Results from analysis of the BRIDGES sequencing dataset.

Author

Davidson AL, Michailidou K, Parsons MT, Fortuno C, Bolla MK, Wang Q, Dennis J, Naven M, Abubakar M, Ahearn TU, Alonso MR, Andrulis IL, Antoniou AC, Auvinen P, Behrens S, Bermisheva MA, Bogdanova NV, Bojesen SE, Brüning T, Byers HJ, Camp NJ, Campbell A, Castelao JE, Cessna MH, Chang-Claude J, Chanock SJ, Chenevix-Trench G, Collée JM, Czene K, Dörk T, Eriksson M, Evans DG, Fasching PA, Figueroa JD, Flyger H, Gago-Dominguez M, García-Closas M, Glendon G, González-Neira A, Grassmann F, Gronwald J, Guénel P, Hadjisavvas A, Haeberle L, Hall P, Hamann U, Hartman M, Ho PJ, Hooning MJ, Hoppe R, Howell A, Jakubowska A, Khusnutdinova EK, Kristensen VN, Li J, Lim J, Lindblom A, Liu J, Lophatananon A, Mannermaa A, Mavroudis DA, Mensenkamp AR, Milne RL, Muir KR, Newman WG, Obi N, Panayiotidis MI, Park SK, Park-Simon TW, Peterlongo P, Radice P, Rashid MU, Rhenius V, Saloustros E, Sawyer EJ, Schmidt MK, Seibold P, Shah M, Southey MC, Teo SH, Tomlinson I, Torres D, Truong T, van de Beek I, van der Hout AH, Wendt CC, Dunning AM, Pharoah PDP, Devilee P, Easton DF, James PA, and Spurdle AB

Subjects
Humans, Female, BRCA2 Protein genetics, BRCA1 Protein genetics, Fanconi Anemia Complementation Group N Protein genetics, Middle Aged, Mutation, Missense genetics, Adult, Tumor Suppressor Protein p53 genetics, Breast Neoplasms genetics, Genetic Predisposition to Disease, Germ-Line Mutation genetics
Abstract

Co-observation of a gene variant with a pathogenic variant in another gene that explains the disease presentation has been designated as evidence against pathogenicity for commonly used variant classification guidelines. Multiple variant curation expert panels have specified, from consensus opinion, that this evidence type is not applicable for the classification of breast cancer predisposition gene variants. Statistical analysis of sequence data for 55,815 individuals diagnosed with breast cancer from the BRIDGES sequencing project was undertaken to formally assess the utility of co-observation data for germline variant classification. Our analysis included expected loss-of-function variants in 11 breast cancer predisposition genes and pathogenic missense variants in BRCA1, BRCA2, and TP53. We assessed whether co-observation of pathogenic variants in two different genes occurred more or less often than expected under the assumption of independence. Co-observation of pathogenic variants in each of BRCA1, BRCA2, and PALB2 with the remaining genes was less frequent than expected. This evidence for depletion remained after adjustment for age at diagnosis, study design (familial versus population-based), and country. Co-observation of a variant of uncertain significance in BRCA1, BRCA2, or PALB2 with a pathogenic variant in another breast cancer gene equated to supporting evidence against pathogenicity following criterion strength assignment based on the likelihood ratio and showed utility in reclassification of missense BRCA1 and BRCA2 variants identified in BRIDGES. Our approach has applicability for assessing the value of co-observation as a predictor of variant pathogenicity in other clinical contexts, including for gene-specific guidelines developed by ClinGen Variant Curation Expert Panels., Competing Interests: Declaration of interests P.A.F. conducts research funded by Amgen, Novartis, and Pfizer. He received Honoraria from Roche, Novartis, and Pfizer. A.R.M. received funds from AstraZeneca for contribution to sponsored quality assessments and variant interpretation of VUSs in BRCA1 and BRCA2. The funds were paid to the institution., (Copyright © 2024 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2024
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3. The impact of coding germline variants on contralateral breast cancer risk and survival.

Author

Morra A, Mavaddat N, Muranen TA, Ahearn TU, Allen J, Andrulis IL, Auvinen P, Becher H, Behrens S, Blomqvist C, Bojesen SE, Bolla MK, Brauch H, Camp NJ, Carvalho S, Castelao JE, Cessna MH, Chang-Claude J, Chenevix-Trench G, Czene K, Decker B, Dennis J, Dörk T, Dorling L, Dunning AM, Ekici AB, Eriksson M, Evans DG, Fasching PA, Figueroa JD, Flyger H, Gago-Dominguez M, García-Closas M, Geurts-Giele WRR, Giles GG, Guénel P, Gündert M, Hahnen E, Hall P, Hamann U, Harrington PA, He W, Heikkilä P, Hooning MJ, Hoppe R, Howell A, Humphreys K, Jakubowska A, Jung AY, Keeman R, Kristensen VN, Lubiński J, Mannermaa A, Manoochehri M, Manoukian S, Margolin S, Mavroudis D, Milne RL, Mulligan AM, Newman WG, Park-Simon TW, Peterlongo P, Pharoah PDP, Rhenius V, Saloustros E, Sawyer EJ, Schmutzler RK, Shah M, Spurdle AB, Tomlinson I, Truong T, van Veen EM, Vreeswijk MPG, Wang Q, Wendt C, Yang XR, Nevanlinna H, Devilee P, Easton DF, and Schmidt MK

Subjects
Female, Humans, Genes, BRCA2, Germ-Line Mutation, Germ Cells, Genetic Predisposition to Disease, Breast Neoplasms genetics
Abstract

Evidence linking coding germline variants in breast cancer (BC)-susceptibility genes other than BRCA1, BRCA2, and CHEK2 with contralateral breast cancer (CBC) risk and breast cancer-specific survival (BCSS) is scarce. The aim of this study was to assess the association of protein-truncating variants (PTVs) and rare missense variants (MSVs) in nine known (ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53) and 25 suspected BC-susceptibility genes with CBC risk and BCSS. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated with Cox regression models. Analyses included 34,401 women of European ancestry diagnosed with BC, including 676 CBCs and 3,449 BC deaths; the median follow-up was 10.9 years. Subtype analyses were based on estrogen receptor (ER) status of the first BC. Combined PTVs and pathogenic/likely pathogenic MSVs in BRCA1, BRCA2, and TP53 and PTVs in CHEK2 and PALB2 were associated with increased CBC risk [HRs (95% CIs): 2.88 (1.70-4.87), 2.31 (1.39-3.85), 8.29 (2.53-27.21), 2.25 (1.55-3.27), and 2.67 (1.33-5.35), respectively]. The strongest evidence of association with BCSS was for PTVs and pathogenic/likely pathogenic MSVs in BRCA2 (ER-positive BC) and TP53 and PTVs in CHEK2 [HRs (95% CIs): 1.53 (1.13-2.07), 2.08 (0.95-4.57), and 1.39 (1.13-1.72), respectively, after adjusting for tumor characteristics and treatment]. HRs were essentially unchanged when censoring for CBC, suggesting that these associations are not completely explained by increased CBC risk, tumor characteristics, or treatment. There was limited evidence of associations of PTVs and/or rare MSVs with CBC risk or BCSS for the 25 suspected BC genes. The CBC findings are relevant to treatment decisions, follow-up, and screening after BC diagnosis., Competing Interests: Declaration of interests B.D. is a stockholder of Roche, Vaccitech and EQRx. P.A.F. conducts research funded by Amgen, Novartis, and Pfizer outside the submitted work. He received honoraria from Roche, Novartis, and Pfizer outside the submitted work. D.F.E. is an associate editor at The American Journal of Human Genetics (AJHG)., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2023
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4. Genome- and transcriptome-wide association studies of 386,000 Asian and European-ancestry women provide new insights into breast cancer genetics.

Author

Jia G, Ping J, Shu X, Yang Y, Cai Q, Kweon SS, Choi JY, Kubo M, Park SK, Bolla MK, Dennis J, Wang Q, Guo X, Li B, Tao R, Aronson KJ, Chan TL, Gao YT, Hartman M, Ho WK, Ito H, Iwasaki M, Iwata H, John EM, Kasuga Y, Kim MK, Kurian AW, Kwong A, Li J, Lophatananon A, Low SK, Mariapun S, Matsuda K, Matsuo K, Muir K, Noh DY, Park B, Park MH, Shen CY, Shin MH, Spinelli JJ, Takahashi A, Tseng C, Tsugane S, Wu AH, Yamaji T, Zheng Y, Dunning AM, Pharoah PDP, Teo SH, Kang D, Easton DF, Simard J, Shu XO, Long J, and Zheng W

Subjects
Female, Humans, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide genetics, Transcriptome genetics, Case-Control Studies, Genome-Wide Association Study, Breast Neoplasms genetics
Abstract

By combining data from 160,500 individuals with breast cancer and 226,196 controls of Asian and European ancestry, we conducted genome- and transcriptome-wide association studies of breast cancer. We identified 222 genetic risk loci and 137 genes that were associated with breast cancer risk at a p < 5.0 × 10 -8 and a Bonferroni-corrected p < 4.6 × 10 -6 , respectively. Of them, 32 loci and 15 genes showed a significantly different association between ER-positive and ER-negative breast cancer after Bonferroni correction. Significant ancestral differences in risk variant allele frequencies and their association strengths with breast cancer risk were identified. Of the significant associations identified in this study, 17 loci and 14 genes are located 1Mb away from any of the previously reported breast cancer risk variants. Pathways analyses including 221 putative risk genes identified multiple signaling pathways that may play a significant role in the development of breast cancer. Our study provides a comprehensive understanding of and new biological insights into the genetics of this common malignancy., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2022
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5. Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction.

Author

Li S, MacInnis RJ, Lee A, Nguyen-Dumont T, Dorling L, Carvalho S, Dite GS, Shah M, Luccarini C, Wang Q, Milne RL, Jenkins MA, Giles GG, Dunning AM, Pharoah PDP, Southey MC, Easton DF, Hopper JL, and Antoniou AC

Subjects
Adult, Aged, 80 and over, Case-Control Studies, Female, Humans, Multifactorial Inheritance genetics, Penetrance, Young Adult, Breast Neoplasms epidemiology, Breast Neoplasms genetics, Genetic Predisposition to Disease
Abstract

Rare pathogenic variants in known breast cancer-susceptibility genes and known common susceptibility variants do not fully explain the familial aggregation of breast cancer. To investigate plausible genetic models for the residual familial aggregation, we studied 17,425 families ascertained through population-based probands, 86% of whom were screened for pathogenic variants in BRCA1, BRCA2, PALB2, CHEK2, ATM, and TP53 via gene-panel sequencing. We conducted complex segregation analyses and fitted genetic models in which breast cancer incidence depended on the effects of known susceptibility genes and other unidentified major genes and a normally distributed polygenic component. The proportion of familial variance explained by the six genes was 46% at age 20-29 years and decreased steadily with age thereafter. After allowing for these genes, the best fitting model for the residual familial variance included a recessive risk component with a combined genotype frequency of 1.7% (95% CI: 0.3%-5.4%) and a penetrance to age 80 years of 69% (95% CI: 38%-95%) for homozygotes, which may reflect the combined effects of multiple variants acting in a recessive manner, and a polygenic variance of 1.27 (95% CI: 0.94%-1.65), which did not vary with age. The proportion of the residual familial variance explained by the recessive risk component was 40% at age 20-29 years and decreased with age thereafter. The model predicted age-specific familial relative risks consistent with those observed by large epidemiological studies. The findings have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age., Competing Interests: Declaration of interests A.C.A., A.L., and D.F.E. are listed as creators of BOADICEA v.5, which has been licensed by Cambridge Enterprise. G.D.S. is an employee of Genetic Technologies Ltd., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Published
2022
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6. Functional annotation of the 2q35 breast cancer risk locus implicates a structural variant in influencing activity of a long-range enhancer element.

Author

Baxter JS, Johnson N, Tomczyk K, Gillespie A, Maguire S, Brough R, Fachal L, Michailidou K, Bolla MK, Wang Q, Dennis J, Ahearn TU, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Augustinsson A, Becher H, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Bogdanova NV, Bojesen SE, Brenner H, Brucker SY, Cai Q, Campa D, Canzian F, Castelao JE, Chan TL, Chang-Claude J, Chanock SJ, Chenevix-Trench G, Choi JY, Clarke CL, Colonna S, Conroy DM, Couch FJ, Cox A, Cross SS, Czene K, Daly MB, Devilee P, Dörk T, Dossus L, Dwek M, Eccles DM, Ekici AB, Eliassen AH, Engel C, Fasching PA, Figueroa J, Flyger H, Gago-Dominguez M, Gao C, García-Closas M, García-Sáenz JA, Ghoussaini M, Giles GG, Goldberg MS, González-Neira A, Guénel P, Gündert M, Haeberle L, Hahnen E, Haiman CA, Hall P, Hamann U, Hartman M, Hatse S, Hauke J, Hollestelle A, Hoppe R, Hopper JL, Hou MF, Ito H, Iwasaki M, Jager A, Jakubowska A, Janni W, John EM, Joseph V, Jung A, Kaaks R, Kang D, Keeman R, Khusnutdinova E, Kim SW, Kosma VM, Kraft P, Kristensen VN, Kubelka-Sabit K, Kurian AW, Kwong A, Lacey JV, Lambrechts D, Larson NL, Larsson SC, Le Marchand L, Lejbkowicz F, Li J, Long J, Lophatananon A, Lubiński J, Mannermaa A, Manoochehri M, Manoukian S, Margolin S, Matsuo K, Mavroudis D, Mayes R, Menon U, Milne RL, Mohd Taib NA, Muir K, Muranen TA, Murphy RA, Nevanlinna H, O'Brien KM, Offit K, Olson JE, Olsson H, Park SK, Park-Simon TW, Patel AV, Peterlongo P, Peto J, Plaseska-Karanfilska D, Presneau N, Pylkäs K, Rack B, Rennert G, Romero A, Ruebner M, Rüdiger T, Saloustros E, Sandler DP, Sawyer EJ, Schmidt MK, Schmutzler RK, Schneeweiss A, Schoemaker MJ, Shah M, Shen CY, Shu XO, Simard J, Southey MC, Stone J, Surowy H, Swerdlow AJ, Tamimi RM, Tapper WJ, Taylor JA, Teo SH, Teras LR, Terry MB, Toland AE, Tomlinson I, Truong T, Tseng CC, Untch M, Vachon CM, van den Ouweland AMW, Wang SS, Weinberg CR, Wendt C, Winham SJ, Winqvist R, Wolk A, Wu AH, Yamaji T, Zheng W, Ziogas A, Pharoah PDP, Dunning AM, Easton DF, Pettitt SJ, Lord CJ, Haider S, Orr N, and Fletcher O

Subjects
Breast Neoplasms genetics, CRISPR-Cas Systems, Cell Line, Chromosome Mapping, Chromosomes, Human, Pair 2, Female, Genetic Association Studies, Genetic Variation, Humans, Risk Factors, Sequence Deletion, Insulin-Like Growth Factor Binding Protein 5 genetics, Molecular Sequence Annotation, Promoter Regions, Genetic
Abstract

A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10 -31 )., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2021
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7. Breast Cancer Polygenic Risk Score and Contralateral Breast Cancer Risk.

Author

Kramer I, Hooning MJ, Mavaddat N, Hauptmann M, Keeman R, Steyerberg EW, Giardiello D, Antoniou AC, Pharoah PDP, Canisius S, Abu-Ful Z, Andrulis IL, Anton-Culver H, Aronson KJ, Augustinsson A, Becher H, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Bogdanova NV, Bojesen SE, Bolla MK, Bonanni B, Brauch H, Bremer M, Brucker SY, Burwinkel B, Castelao JE, Chan TL, Chang-Claude J, Chanock SJ, Chenevix-Trench G, Choi JY, Clarke CL, Collée JM, Couch FJ, Cox A, Cross SS, Czene K, Daly MB, Devilee P, Dörk T, Dos-Santos-Silva I, Dunning AM, Dwek M, Eccles DM, Evans DG, Fasching PA, Flyger H, Gago-Dominguez M, García-Closas M, García-Sáenz JA, Giles GG, Goldgar DE, González-Neira A, Haiman CA, Håkansson N, Hamann U, Hartman M, Heemskerk-Gerritsen BAM, Hollestelle A, Hopper JL, Hou MF, Howell A, Ito H, Jakimovska M, Jakubowska A, Janni W, John EM, Jung A, Kang D, Kets CM, Khusnutdinova E, Ko YD, Kristensen VN, Kurian AW, Kwong A, Lambrechts D, Le Marchand L, Li J, Lindblom A, Lubiński J, Mannermaa A, Manoochehri M, Margolin S, Matsuo K, Mavroudis D, Meindl A, Milne RL, Mulligan AM, Muranen TA, Neuhausen SL, Nevanlinna H, Newman WG, Olshan AF, Olson JE, Olsson H, Park-Simon TW, Peto J, Petridis C, Plaseska-Karanfilska D, Presneau N, Pylkäs K, Radice P, Rennert G, Romero A, Roylance R, Saloustros E, Sawyer EJ, Schmutzler RK, Schwentner L, Scott C, See MH, Shah M, Shen CY, Shu XO, Siesling S, Slager S, Sohn C, Southey MC, Spinelli JJ, Stone J, Tapper WJ, Tengström M, Teo SH, Terry MB, Tollenaar RAEM, Tomlinson I, Troester MA, Vachon CM, van Ongeval C, van Veen EM, Winqvist R, Wolk A, Zheng W, Ziogas A, Easton DF, Hall P, and Schmidt MK

Subjects
Adult, Aged, Asian People, Breast Neoplasms diagnosis, Breast Neoplasms ethnology, Breast Neoplasms therapy, Cohort Studies, Estrogen Receptor alpha genetics, Estrogen Receptor alpha metabolism, Female, Gene Expression, Genome-Wide Association Study, Humans, Middle Aged, Neoadjuvant Therapy methods, Neoplasms, Second Primary diagnosis, Neoplasms, Second Primary ethnology, Neoplasms, Second Primary therapy, Prognosis, Proportional Hazards Models, Receptor, ErbB-2 genetics, Receptor, ErbB-2 metabolism, Receptors, Progesterone genetics, Receptors, Progesterone metabolism, Risk Assessment, White People, Breast Neoplasms genetics, Genetic Predisposition to Disease, Genome, Human, Multifactorial Inheritance, Neoplasms, Second Primary genetics
Abstract

Previous research has shown that polygenic risk scores (PRSs) can be used to stratify women according to their risk of developing primary invasive breast cancer. This study aimed to evaluate the association between a recently validated PRS of 313 germline variants (PRS 313 ) and contralateral breast cancer (CBC) risk. We included 56,068 women of European ancestry diagnosed with first invasive breast cancer from 1990 onward with follow-up from the Breast Cancer Association Consortium. Metachronous CBC risk (N = 1,027) according to the distribution of PRS 313 was quantified using Cox regression analyses. We assessed PRS 313 interaction with age at first diagnosis, family history, morphology, ER status, PR status, and HER2 status, and (neo)adjuvant therapy. In studies of Asian women, with limited follow-up, CBC risk associated with PRS 313 was assessed using logistic regression for 340 women with CBC compared with 12,133 women with unilateral breast cancer. Higher PRS 313 was associated with increased CBC risk: hazard ratio per standard deviation (SD) = 1.25 (95%CI = 1.18-1.33) for Europeans, and an OR per SD = 1.15 (95%CI = 1.02-1.29) for Asians. The absolute lifetime risks of CBC, accounting for death as competing risk, were 12.4% for European women at the 10 th percentile and 20.5% at the 90 th percentile of PRS 313 . We found no evidence of confounding by or interaction with individual characteristics, characteristics of the primary tumor, or treatment. The C-index for the PRS 313 alone was 0.563 (95%CI = 0.547-0.586). In conclusion, PRS 313 is an independent factor associated with CBC risk and can be incorporated into CBC risk prediction models to help improve stratification and optimize surveillance and treatment strategies., (Copyright © 2020 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2020
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8. Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.

Author

Mavaddat N, Michailidou K, Dennis J, Lush M, Fachal L, Lee A, Tyrer JP, Chen TH, Wang Q, Bolla MK, Yang X, Adank MA, Ahearn T, Aittomäki K, Allen J, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Auer PL, Auvinen P, Barrdahl M, Beane Freeman LE, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Bernstein L, Blomqvist C, Bogdanova NV, Bojesen SE, Bonanni B, Børresen-Dale AL, Brauch H, Bremer M, Brenner H, Brentnall A, Brock IW, Brooks-Wilson A, Brucker SY, Brüning T, Burwinkel B, Campa D, Carter BD, Castelao JE, Chanock SJ, Chlebowski R, Christiansen H, Clarke CL, Collée JM, Cordina-Duverger E, Cornelissen S, Couch FJ, Cox A, Cross SS, Czene K, Daly MB, Devilee P, Dörk T, Dos-Santos-Silva I, Dumont M, Durcan L, Dwek M, Eccles DM, Ekici AB, Eliassen AH, Ellberg C, Engel C, Eriksson M, Evans DG, Fasching PA, Figueroa J, Fletcher O, Flyger H, Försti A, Fritschi L, Gabrielson M, Gago-Dominguez M, Gapstur SM, García-Sáenz JA, Gaudet MM, Georgoulias V, Giles GG, Gilyazova IR, Glendon G, Goldberg MS, Goldgar DE, González-Neira A, Grenaker Alnæs GI, Grip M, Gronwald J, Grundy A, Guénel P, Haeberle L, Hahnen E, Haiman CA, Håkansson N, Hamann U, Hankinson SE, Harkness EF, Hart SN, He W, Hein A, Heyworth J, Hillemanns P, Hollestelle A, Hooning MJ, Hoover RN, Hopper JL, Howell A, Huang G, Humphreys K, Hunter DJ, Jakimovska M, Jakubowska A, Janni W, John EM, Johnson N, Jones ME, Jukkola-Vuorinen A, Jung A, Kaaks R, Kaczmarek K, Kataja V, Keeman R, Kerin MJ, Khusnutdinova E, Kiiski JI, Knight JA, Ko YD, Kosma VM, Koutros S, Kristensen VN, Krüger U, Kühl T, Lambrechts D, Le Marchand L, Lee E, Lejbkowicz F, Lilyquist J, Lindblom A, Lindström S, Lissowska J, Lo WY, Loibl S, Long J, Lubiński J, Lux MP, MacInnis RJ, Maishman T, Makalic E, Maleva Kostovska I, Mannermaa A, Manoukian S, Margolin S, Martens JWM, Martinez ME, Mavroudis D, McLean C, Meindl A, Menon U, Middha P, Miller N, Moreno F, Mulligan AM, Mulot C, Muñoz-Garzon VM, Neuhausen SL, Nevanlinna H, Neven P, Newman WG, Nielsen SF, Nordestgaard BG, Norman A, Offit K, Olson JE, Olsson H, Orr N, Pankratz VS, Park-Simon TW, Perez JIA, Pérez-Barrios C, Peterlongo P, Peto J, Pinchev M, Plaseska-Karanfilska D, Polley EC, Prentice R, Presneau N, Prokofyeva D, Purrington K, Pylkäs K, Rack B, Radice P, Rau-Murthy R, Rennert G, Rennert HS, Rhenius V, Robson M, Romero A, Ruddy KJ, Ruebner M, Saloustros E, Sandler DP, Sawyer EJ, Schmidt DF, Schmutzler RK, Schneeweiss A, Schoemaker MJ, Schumacher F, Schürmann P, Schwentner L, Scott C, Scott RJ, Seynaeve C, Shah M, Sherman ME, Shrubsole MJ, Shu XO, Slager S, Smeets A, Sohn C, Soucy P, Southey MC, Spinelli JJ, Stegmaier C, Stone J, Swerdlow AJ, Tamimi RM, Tapper WJ, Taylor JA, Terry MB, Thöne K, Tollenaar RAEM, Tomlinson I, Truong T, Tzardi M, Ulmer HU, Untch M, Vachon CM, van Veen EM, Vijai J, Weinberg CR, Wendt C, Whittemore AS, Wildiers H, Willett W, Winqvist R, Wolk A, Yang XR, Yannoukakos D, Zhang Y, Zheng W, Ziogas A, Dunning AM, Thompson DJ, Chenevix-Trench G, Chang-Claude J, Schmidt MK, Hall P, Milne RL, Pharoah PDP, Antoniou AC, Chatterjee N, Kraft P, García-Closas M, Simard J, and Easton DF

Subjects
Adult, Age Factors, Aged, Aged, 80 and over, Breast Neoplasms diagnosis, Breast Neoplasms prevention & control, Female, Humans, Medical History Taking, Middle Aged, Polymorphism, Single Nucleotide genetics, Receptors, Estrogen metabolism, Reproducibility of Results, Risk Assessment, Breast Neoplasms classification, Breast Neoplasms genetics, Genetic Predisposition to Disease, Multifactorial Inheritance genetics
Abstract

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2019
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9. Evidence that the 5p12 Variant rs10941679 Confers Susceptibility to Estrogen-Receptor-Positive Breast Cancer through FGF10 and MRPS30 Regulation.

Author

Ghoussaini M, French JD, Michailidou K, Nord S, Beesley J, Canisus S, Hillman KM, Kaufmann S, Sivakumaran H, Moradi Marjaneh M, Lee JS, Dennis J, Bolla MK, Wang Q, Dicks E, Milne RL, Hopper JL, Southey MC, Schmidt MK, Broeks A, Muir K, Lophatananon A, Fasching PA, Beckmann MW, Fletcher O, Johnson N, Sawyer EJ, Tomlinson I, Burwinkel B, Marme F, Guénel P, Truong T, Bojesen SE, Flyger H, Benitez J, González-Neira A, Alonso MR, Pita G, Neuhausen SL, Anton-Culver H, Brenner H, Arndt V, Meindl A, Schmutzler RK, Brauch H, Hamann U, Tessier DC, Vincent D, Nevanlinna H, Khan S, Matsuo K, Ito H, Dörk T, Bogdanova NV, Lindblom A, Margolin S, Mannermaa A, Kosma VM, Wu AH, Van Den Berg D, Lambrechts D, Floris G, Chang-Claude J, Rudolph A, Radice P, Barile M, Couch FJ, Hallberg E, Giles GG, Haiman CA, Le Marchand L, Goldberg MS, Teo SH, Yip CH, Borresen-Dale AL, Zheng W, Cai Q, Winqvist R, Pylkäs K, Andrulis IL, Devilee P, Tollenaar RA, García-Closas M, Figueroa J, Hall P, Czene K, Brand JS, Darabi H, Eriksson M, Hooning MJ, Koppert LB, Li J, Shu XO, Zheng Y, Cox A, Cross SS, Shah M, Rhenius V, Choi JY, Kang D, Hartman M, Chia KS, Kabisch M, Torres D, Luccarini C, Conroy DM, Jakubowska A, Lubinski J, Sangrajrang S, Brennan P, Olswold C, Slager S, Shen CY, Hou MF, Swerdlow A, Schoemaker MJ, Simard J, Pharoah PD, Kristensen V, Chenevix-Trench G, Easton DF, Dunning AM, and Edwards SL

Subjects
Alleles, Case-Control Studies, Cell Line, Tumor, Enhancer Elements, Genetic genetics, Fibroblast Growth Factor 10 metabolism, Haplotypes genetics, Humans, Promoter Regions, Genetic genetics, Quantitative Trait Loci genetics, Receptor, Fibroblast Growth Factor, Type 2 metabolism, Breast Neoplasms genetics, Breast Neoplasms metabolism, Chromosomes, Human, Pair 5 genetics, Fibroblast Growth Factor 10 genetics, Genetic Predisposition to Disease genetics, Polymorphism, Single Nucleotide genetics, Receptors, Estrogen metabolism
Abstract

Genome-wide association studies (GWASs) have revealed increased breast cancer risk associated with multiple genetic variants at 5p12. Here, we report the fine mapping of this locus using data from 104,660 subjects from 50 case-control studies in the Breast Cancer Association Consortium (BCAC). With data for 3,365 genotyped and imputed SNPs across a 1 Mb region (positions 44,394,495-45,364,167; NCBI build 37), we found evidence for at least three independent signals: the strongest signal, consisting of a single SNP rs10941679, was associated with risk of estrogen-receptor-positive (ER + ) breast cancer (per-g allele OR ER + = 1.15; 95% CI 1.13-1.18; p = 8.35 × 10 -30 ). After adjustment for rs10941679, we detected signal 2, consisting of 38 SNPs more strongly associated with ER-negative (ER - ) breast cancer (lead SNP rs6864776: per-a allele OR ER - = 1.10; 95% CI 1.05-1.14; p conditional = 1.44 × 10 -12 ), and a single signal 3 SNP (rs200229088: per-t allele OR ER + = 1.12; 95% CI 1.09-1.15; p conditional = 1.12 × 10 -05 ). Expression quantitative trait locus analysis in normal breast tissues and breast tumors showed that the g (risk) allele of rs10941679 was associated with increased expression of FGF10 and MRPS30. Functional assays demonstrated that SNP rs10941679 maps to an enhancer element that physically interacts with the FGF10 and MRPS30 promoter regions in breast cancer cell lines. FGF10 is an oncogene that binds to FGFR2 and is overexpressed in ∼10% of human breast cancers, whereas MRPS30 plays a key role in apoptosis. These data suggest that the strongest signal of association at 5p12 is mediated through coordinated activation of FGF10 and MRPS30, two candidate genes for breast cancer pathogenesis., (Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.)

Published
2016
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10. Polymorphisms in a Putative Enhancer at the 10q21.2 Breast Cancer Risk Locus Regulate NRBF2 Expression.

Author

Darabi H, McCue K, Beesley J, Michailidou K, Nord S, Kar S, Humphreys K, Thompson D, Ghoussaini M, Bolla MK, Dennis J, Wang Q, Canisius S, Scott CG, Apicella C, Hopper JL, Southey MC, Stone J, Broeks A, Schmidt MK, Scott RJ, Lophatananon A, Muir K, Beckmann MW, Ekici AB, Fasching PA, Heusinger K, Dos-Santos-Silva I, Peto J, Tomlinson I, Sawyer EJ, Burwinkel B, Marme F, Guénel P, Truong T, Bojesen SE, Flyger H, Benitez J, González-Neira A, Anton-Culver H, Neuhausen SL, Arndt V, Brenner H, Engel C, Meindl A, Schmutzler RK, Arnold N, Brauch H, Hamann U, Chang-Claude J, Khan S, Nevanlinna H, Ito H, Matsuo K, Bogdanova NV, Dörk T, Lindblom A, Margolin S, Kosma VM, Mannermaa A, Tseng CC, Wu AH, Floris G, Lambrechts D, Rudolph A, Peterlongo P, Radice P, Couch FJ, Vachon C, Giles GG, McLean C, Milne RL, Dugué PA, Haiman CA, Maskarinec G, Woolcott C, Henderson BE, Goldberg MS, Simard J, Teo SH, Mariapun S, Helland Å, Haakensen V, Zheng W, Beeghly-Fadiel A, Tamimi R, Jukkola-Vuorinen A, Winqvist R, Andrulis IL, Knight JA, Devilee P, Tollenaar RA, Figueroa J, García-Closas M, Czene K, Hooning MJ, Tilanus-Linthorst M, Li J, Gao YT, Shu XO, Cox A, Cross SS, Luben R, Khaw KT, Choi JY, Kang D, Hartman M, Lim WY, Kabisch M, Torres D, Jakubowska A, Lubinski J, McKay J, Sangrajrang S, Toland AE, Yannoukakos D, Shen CY, Yu JC, Ziogas A, Schoemaker MJ, Swerdlow A, Borresen-Dale AL, Kristensen V, French JD, Edwards SL, Dunning AM, Easton DF, Hall P, and Chenevix-Trench G

Subjects
Age Factors, Asian People genetics, Autophagy-Related Proteins, Body Mass Index, Chromosome Mapping, Female, Genome-Wide Association Study, Genotype, Humans, Luciferases, Odds Ratio, Polymorphism, Single Nucleotide genetics, Quantitative Trait Loci genetics, Regression Analysis, Trans-Activators metabolism, White People genetics, Breast Neoplasms genetics, Chromosomes, Human, Pair 10 genetics, DNA-Binding Proteins genetics, Enhancer Elements, Genetic genetics, Gene Expression Regulation genetics, Trans-Activators genetics, Transcription Factors genetics
Abstract

Genome-wide association studies have identified SNPs near ZNF365 at 10q21.2 that are associated with both breast cancer risk and mammographic density. To identify the most likely causal SNPs, we fine mapped the association signal by genotyping 428 SNPs across the region in 89,050 European and 12,893 Asian case and control subjects from the Breast Cancer Association Consortium. We identified four independent sets of correlated, highly trait-associated variants (iCHAVs), three of which were located within ZNF365. The most strongly risk-associated SNP, rs10995201 in iCHAV1, showed clear evidence of association with both estrogen receptor (ER)-positive (OR = 0.85 [0.82-0.88]) and ER-negative (OR = 0.87 [0.82-0.91]) disease, and was also the SNP most strongly associated with percent mammographic density. iCHAV2 (lead SNP, chr10: 64,258,684:D) and iCHAV3 (lead SNP, rs7922449) were also associated with ER-positive (OR = 0.93 [0.91-0.95] and OR = 1.06 [1.03-1.09]) and ER-negative (OR = 0.95 [0.91-0.98] and OR = 1.08 [1.04-1.13]) disease. There was weaker evidence for iCHAV4, located 5' of ADO, associated only with ER-positive breast cancer (OR = 0.93 [0.90-0.96]). We found 12, 17, 18, and 2 candidate causal SNPs for breast cancer in iCHAVs 1-4, respectively. Chromosome conformation capture analysis showed that iCHAV2 interacts with the ZNF365 and NRBF2 (more than 600 kb away) promoters in normal and cancerous breast epithelial cells. Luciferase assays did not identify SNPs that affect transactivation of ZNF365, but identified a protective haplotype in iCHAV2, associated with silencing of the NRBF2 promoter, implicating this gene in the etiology of breast cancer., (Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2015
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11. Fine-scale mapping of the 5q11.2 breast cancer locus reveals at least three independent risk variants regulating MAP3K1.

Author

Glubb DM, Maranian MJ, Michailidou K, Pooley KA, Meyer KB, Kar S, Carlebur S, O'Reilly M, Betts JA, Hillman KM, Kaufmann S, Beesley J, Canisius S, Hopper JL, Southey MC, Tsimiklis H, Apicella C, Schmidt MK, Broeks A, Hogervorst FB, van der Schoot CE, Muir K, Lophatananon A, Stewart-Brown S, Siriwanarangsan P, Fasching PA, Ruebner M, Ekici AB, Beckmann MW, Peto J, dos-Santos-Silva I, Fletcher O, Johnson N, Pharoah PD, Bolla MK, Wang Q, Dennis J, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Burwinkel B, Marme F, Yang R, Surowy H, Guénel P, Truong T, Menegaux F, Sanchez M, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, González-Neira A, Benitez J, Zamora MP, Arias Perez JI, Anton-Culver H, Neuhausen SL, Brenner H, Dieffenbach AK, Arndt V, Stegmaier C, Meindl A, Schmutzler RK, Brauch H, Ko YD, Brüning T, Nevanlinna H, Muranen TA, Aittomäki K, Blomqvist C, Matsuo K, Ito H, Iwata H, Tanaka H, Dörk T, Bogdanova NV, Helbig S, Lindblom A, Margolin S, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Wu AH, Tseng CC, Van Den Berg D, Stram DO, Lambrechts D, Zhao H, Weltens C, van Limbergen E, Chang-Claude J, Flesch-Janys D, Rudolph A, Seibold P, Radice P, Peterlongo P, Barile M, Capra F, Couch FJ, Olson JE, Hallberg E, Vachon C, Giles GG, Milne RL, McLean C, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Simard J, Goldberg MS, Labrèche F, Dumont M, Teo SH, Yip CH, See MH, Cornes B, Cheng CY, Ikram MK, Kristensen V, Zheng W, Halverson SL, Shrubsole M, Long J, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Kauppila S, Andrulis IL, Knight JA, Glendon G, Tchatchou S, Devilee P, Tollenaar RA, Seynaeve C, Van Asperen CJ, García-Closas M, Figueroa J, Chanock SJ, Lissowska J, Czene K, Klevebring D, Darabi H, Eriksson M, Hooning MJ, Hollestelle A, Martens JW, Collée JM, Hall P, Li J, Humphreys K, Shu XO, Lu W, Gao YT, Cai H, Cox A, Cross SS, Reed MW, Blot W, Signorello LB, Cai Q, Shah M, Ghoussaini M, Kang D, Choi JY, Park SK, Noh DY, Hartman M, Miao H, Lim WY, Tang A, Hamann U, Torres D, Jakubowska A, Lubinski J, Jaworska K, Durda K, Sangrajrang S, Gaborieau V, Brennan P, McKay J, Olswold C, Slager S, Toland AE, Yannoukakos D, Shen CY, Wu PE, Yu JC, Hou MF, Swerdlow A, Ashworth A, Orr N, Jones M, Pita G, Alonso MR, Álvarez N, Herrero D, Tessier DC, Vincent D, Bacot F, Luccarini C, Baynes C, Ahmed S, Healey CS, Brown MA, Ponder BA, Chenevix-Trench G, Thompson DJ, Edwards SL, Easton DF, Dunning AM, and French JD

Subjects
Alleles, Case-Control Studies, Cell Line, Tumor, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotyping Techniques, Humans, MAP Kinase Kinase Kinase 1 metabolism, MCF-7 Cells, Polymorphism, Single Nucleotide, Promoter Regions, Genetic, Racial Groups genetics, Risk Factors, Breast Neoplasms genetics, Chromosome Mapping, Chromosomes, Human, Pair 5 genetics, MAP Kinase Kinase Kinase 1 genetics, Quantitative Trait Loci
Abstract

Genome-wide association studies (GWASs) have revealed SNP rs889312 on 5q11.2 to be associated with breast cancer risk in women of European ancestry. In an attempt to identify the biologically relevant variants, we analyzed 909 genetic variants across 5q11.2 in 103,991 breast cancer individuals and control individuals from 52 studies in the Breast Cancer Association Consortium. Multiple logistic regression analyses identified three independent risk signals: the strongest associations were with 15 correlated variants (iCHAV1), where the minor allele of the best candidate, rs62355902, associated with significantly increased risks of both estrogen-receptor-positive (ER(+): odds ratio [OR] = 1.24, 95% confidence interval [CI] = 1.21-1.27, ptrend = 5.7 × 10(-44)) and estrogen-receptor-negative (ER(-): OR = 1.10, 95% CI = 1.05-1.15, ptrend = 3.0 × 10(-4)) tumors. After adjustment for rs62355902, we found evidence of association of a further 173 variants (iCHAV2) containing three subsets with a range of effects (the strongest was rs113317823 [pcond = 1.61 × 10(-5)]) and five variants composing iCHAV3 (lead rs11949391; ER(+): OR = 0.90, 95% CI = 0.87-0.93, pcond = 1.4 × 10(-4)). Twenty-six percent of the prioritized candidate variants coincided with four putative regulatory elements that interact with the MAP3K1 promoter through chromatin looping and affect MAP3K1 promoter activity. Functional analysis indicated that the cancer risk alleles of four candidates (rs74345699 and rs62355900 [iCHAV1], rs16886397 [iCHAV2a], and rs17432750 [iCHAV3]) increased MAP3K1 transcriptional activity. Chromatin immunoprecipitation analysis revealed diminished GATA3 binding to the minor (cancer-protective) allele of rs17432750, indicating a mechanism for its action. We propose that the cancer risk alleles act to increase MAP3K1 expression in vivo and might promote breast cancer cell survival., (Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2015
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12. Fine-scale mapping of the FGFR2 breast cancer risk locus: putative functional variants differentially bind FOXA1 and E2F1.

Author

Meyer KB, O'Reilly M, Michailidou K, Carlebur S, Edwards SL, French JD, Prathalingham R, Dennis J, Bolla MK, Wang Q, de Santiago I, Hopper JL, Tsimiklis H, Apicella C, Southey MC, Schmidt MK, Broeks A, Van 't Veer LJ, Hogervorst FB, Muir K, Lophatananon A, Stewart-Brown S, Siriwanarangsan P, Fasching PA, Lux MP, Ekici AB, Beckmann MW, Peto J, Dos Santos Silva I, Fletcher O, Johnson N, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Marme F, Schneeweiss A, Sohn C, Burwinkel B, Guénel P, Truong T, Laurent-Puig P, Menegaux F, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, Milne RL, Zamora MP, Arias JI, Benitez J, Neuhausen S, Anton-Culver H, Ziogas A, Dur CC, Brenner H, Müller H, Arndt V, Stegmaier C, Meindl A, Schmutzler RK, Engel C, Ditsch N, Brauch H, Brüning T, Ko YD, Nevanlinna H, Muranen TA, Aittomäki K, Blomqvist C, Matsuo K, Ito H, Iwata H, Yatabe Y, Dörk T, Helbig S, Bogdanova NV, Lindblom A, Margolin S, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Chenevix-Trench G, Wu AH, Tseng CC, Van Den Berg D, Stram DO, Lambrechts D, Thienpont B, Christiaens MR, Smeets A, Chang-Claude J, Rudolph A, Seibold P, Flesch-Janys D, Radice P, Peterlongo P, Bonanni B, Bernard L, Couch FJ, Olson JE, Wang X, Purrington K, Giles GG, Severi G, Baglietto L, McLean C, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Simard J, Goldberg MS, Labrèche F, Dumont M, Teo SH, Yip CH, Phuah SY, Kristensen V, Grenaker Alnæs G, Børresen-Dale AL, Zheng W, Deming-Halverson S, Shrubsole M, Long J, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Kauppila S, Andrulis IL, Knight JA, Glendon G, Tchatchou S, Devilee P, Tollenaar RA, Seynaeve CM, García-Closas M, Figueroa J, Chanock SJ, Lissowska J, Czene K, Darabi H, Eriksson K, Hooning MJ, Martens JW, van den Ouweland AM, van Deurzen CH, Hall P, Li J, Liu J, Humphreys K, Shu XO, Lu W, Gao YT, Cai H, Cox A, Reed MW, Blot W, Signorello LB, Cai Q, Pharoah PD, Ghoussaini M, Harrington P, Tyrer J, Kang D, Choi JY, Park SK, Noh DY, Hartman M, Hui M, Lim WY, Buhari SA, Hamann U, Försti A, Rüdiger T, Ulmer HU, Jakubowska A, Lubinski J, Jaworska K, Durda K, Sangrajrang S, Gaborieau V, Brennan P, McKay J, Vachon C, Slager S, Fostira F, Pilarski R, Shen CY, Hsiung CN, Wu PE, Hou MF, Swerdlow A, Ashworth A, Orr N, Schoemaker MJ, Ponder BA, Dunning AM, and Easton DF

Subjects
Alleles, Asian People genetics, Binding Sites, Black People genetics, Case-Control Studies, Cell Line, Tumor, Chromatin Immunoprecipitation, E2F1 Transcription Factor genetics, E2F1 Transcription Factor metabolism, Female, Gene Expression Regulation, Neoplastic, Genetic Association Studies, Haplotypes, Hepatocyte Nuclear Factor 3-alpha genetics, Hepatocyte Nuclear Factor 3-alpha metabolism, Humans, Position-Specific Scoring Matrices, Promoter Regions, Genetic, Protein Binding, RNA Interference, Receptor, Fibroblast Growth Factor, Type 2 metabolism, White People genetics, Breast Neoplasms genetics, Breast Neoplasms metabolism, Chromosome Mapping, Genetic Loci, Receptor, Fibroblast Growth Factor, Type 2 genetics
Abstract

The 10q26 locus in the second intron of FGFR2 is the locus most strongly associated with estrogen-receptor-positive breast cancer in genome-wide association studies. We conducted fine-scale mapping in case-control studies genotyped with a custom chip (iCOGS), comprising 41 studies (n = 89,050) of European ancestry, 9 Asian ancestry studies (n = 13,983), and 2 African ancestry studies (n = 2,028) from the Breast Cancer Association Consortium. We identified three statistically independent risk signals within the locus. Within risk signals 1 and 3, genetic analysis identified five and two variants, respectively, highly correlated with the most strongly associated SNPs. By using a combination of genetic fine mapping, data on DNase hypersensitivity, and electrophoretic mobility shift assays to study protein-DNA binding, we identified rs35054928, rs2981578, and rs45631563 as putative functional SNPs. Chromatin immunoprecipitation showed that FOXA1 preferentially bound to the risk-associated allele (C) of rs2981578 and was able to recruit ERα to this site in an allele-specific manner, whereas E2F1 preferentially bound the risk variant of rs35054928. The risk alleles were preferentially found in open chromatin and bound by Ser5 phosphorylated RNA polymerase II, suggesting that the risk alleles are associated with changes in transcription. Chromatin conformation capture demonstrated that the risk region was able to interact with the promoter of FGFR2, the likely target gene of this risk region. A role for FOXA1 in mediating breast cancer susceptibility at this locus is consistent with the finding that the FGFR2 risk locus primarily predisposes to estrogen-receptor-positive disease., (Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2013
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13. Beyond GWASs: illuminating the dark road from association to function.

Author

Edwards SL, Beesley J, French JD, and Dunning AM

Subjects
Animals, Computational Biology, Epigenesis, Genetic, Genetic Loci, Genetic Predisposition to Disease genetics, Humans, Neoplasms genetics, Neoplasms pathology, Phenotype, RNA, Untranslated genetics, Risk Factors, Chromosome Mapping, Genome-Wide Association Study, Polymorphism, Single Nucleotide
Abstract

Genome-wide association studies (GWASs) have enabled the discovery of common genetic variation contributing to normal and pathological traits and clinical drug responses, but recognizing the precise targets of these associations is now the major challenge. Here, we review recent approaches to the functional follow-up of GWAS loci, including fine mapping of GWAS signal(s), prioritization of putative functional SNPs by the integration of genetic epidemiological and bioinformatic methods, and in vitro and in vivo experimental verification of predicted molecular mechanisms for identifying the targeted genes. The majority of GWAS-identified variants fall in noncoding regions of the genome. Therefore, this review focuses on strategies for assessing likely mechanisms affected by noncoding variants; such mechanisms include transcriptional regulation, noncoding RNA function, and epigenetic regulation. These approaches have already accelerated progress from genetic studies to biological knowledge and might ultimately guide the development of prognostic, preventive, and therapeutic measures., (Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2013
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14. Functional variants at the 11q13 risk locus for breast cancer regulate cyclin D1 expression through long-range enhancers.

Author

French JD, Ghoussaini M, Edwards SL, Meyer KB, Michailidou K, Ahmed S, Khan S, Maranian MJ, O'Reilly M, Hillman KM, Betts JA, Carroll T, Bailey PJ, Dicks E, Beesley J, Tyrer J, Maia AT, Beck A, Knoblauch NW, Chen C, Kraft P, Barnes D, González-Neira A, Alonso MR, Herrero D, Tessier DC, Vincent D, Bacot F, Luccarini C, Baynes C, Conroy D, Dennis J, Bolla MK, Wang Q, Hopper JL, Southey MC, Schmidt MK, Broeks A, Verhoef S, Cornelissen S, Muir K, Lophatananon A, Stewart-Brown S, Siriwanarangsan P, Fasching PA, Loehberg CR, Ekici AB, Beckmann MW, Peto J, dos Santos Silva I, Johnson N, Aitken Z, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Marme F, Schneeweiss A, Sohn C, Burwinkel B, Guénel P, Truong T, Laurent-Puig P, Menegaux F, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, Milne RL, Zamora MP, Arias Perez JI, Benitez J, Anton-Culver H, Brenner H, Müller H, Arndt V, Stegmaier C, Meindl A, Lichtner P, Schmutzler RK, Engel C, Brauch H, Hamann U, Justenhoven C, Aaltonen K, Heikkilä P, Aittomäki K, Blomqvist C, Matsuo K, Ito H, Iwata H, Sueta A, Bogdanova NV, Antonenkova NN, Dörk T, Lindblom A, Margolin S, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Wu AH, Tseng CC, Van Den Berg D, Stram DO, Lambrechts D, Peeters S, Smeets A, Floris G, Chang-Claude J, Rudolph A, Nickels S, Flesch-Janys D, Radice P, Peterlongo P, Bonanni B, Sardella D, Couch FJ, Wang X, Pankratz VS, Lee A, Giles GG, Severi G, Baglietto L, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Simard J, Goldberg MS, Labrèche F, Dumont M, Teo SH, Yip CH, Ng CH, Vithana EN, Kristensen V, Zheng W, Deming-Halverson S, Shrubsole M, Long J, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Andrulis IL, Knight JA, Glendon G, Mulligan AM, Devilee P, Seynaeve C, García-Closas M, Figueroa J, Chanock SJ, Lissowska J, Czene K, Klevebring D, Schoof N, Hooning MJ, Martens JW, Collée JM, Tilanus-Linthorst M, Hall P, Li J, Liu J, Humphreys K, Shu XO, Lu W, Gao YT, Cai H, Cox A, Balasubramanian SP, Blot W, Signorello LB, Cai Q, Pharoah PD, Healey CS, Shah M, Pooley KA, Kang D, Yoo KY, Noh DY, Hartman M, Miao H, Sng JH, Sim X, Jakubowska A, Lubinski J, Jaworska-Bieniek K, Durda K, Sangrajrang S, Gaborieau V, McKay J, Toland AE, Ambrosone CB, Yannoukakos D, Godwin AK, Shen CY, Hsiung CN, Wu PE, Chen ST, Swerdlow A, Ashworth A, Orr N, Schoemaker MJ, Ponder BA, Nevanlinna H, Brown MA, Chenevix-Trench G, Easton DF, and Dunning AM

Subjects
Binding Sites, Case-Control Studies, Cell Line, Tumor, Chromatin chemistry, Chromatin genetics, Chromatin Immunoprecipitation, Cyclin D1 metabolism, Electrophoretic Mobility Shift Assay, Female, GATA3 Transcription Factor antagonists & inhibitors, GATA3 Transcription Factor genetics, GATA3 Transcription Factor metabolism, Gene Expression Regulation, Neoplastic, Humans, Luciferases metabolism, Promoter Regions, Genetic genetics, RNA, Messenger genetics, RNA, Small Interfering genetics, Real-Time Polymerase Chain Reaction, Reverse Transcriptase Polymerase Chain Reaction, Silencer Elements, Transcriptional genetics, ets-Domain Protein Elk-4 antagonists & inhibitors, ets-Domain Protein Elk-4 genetics, ets-Domain Protein Elk-4 metabolism, Breast Neoplasms genetics, Chromosomes, Human, Pair 11 genetics, Cyclin D1 genetics, Enhancer Elements, Genetic genetics, Polymorphism, Single Nucleotide genetics
Abstract

Analysis of 4,405 variants in 89,050 European subjects from 41 case-control studies identified three independent association signals for estrogen-receptor-positive tumors at 11q13. The strongest signal maps to a transcriptional enhancer element in which the G allele of the best candidate causative variant rs554219 increases risk of breast cancer, reduces both binding of ELK4 transcription factor and luciferase activity in reporter assays, and may be associated with low cyclin D1 protein levels in tumors. Another candidate variant, rs78540526, lies in the same enhancer element. Risk association signal 2, rs75915166, creates a GATA3 binding site within a silencer element. Chromatin conformation studies demonstrate that these enhancer and silencer elements interact with each other and with their likely target gene, CCND1., (Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2013
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15. The extent of linkage disequilibrium in four populations with distinct demographic histories.

Author

Dunning AM, Durocher F, Healey CS, Teare MD, McBride SE, Carlomagno F, Xu CF, Dawson E, Rhodes S, Ueda S, Lai E, Luben RN, Van Rensburg EJ, Mannermaa A, Kataja V, Rennart G, Dunham I, Purvis I, Easton D, and Ponder BA

Subjects
Africa ethnology, Alleles, Chromosomes, Human, Pair 13 genetics, Chromosomes, Human, Pair 19 genetics, Chromosomes, Human, Pair 22 genetics, Demography, Finland ethnology, Gene Frequency genetics, Genetic Markers genetics, Genotype, Humans, Jews genetics, Polymorphism, Genetic genetics, United Kingdom ethnology, Chromosome Mapping methods, Genetic Predisposition to Disease genetics, Linkage Disequilibrium genetics, Phylogeny
Abstract

The design and feasibility of whole-genome-association studies are critically dependent on the extent of linkage disequilibrium (LD) between markers. Although there has been extensive theoretical discussion of this, few empirical data exist. The authors have determined the extent of LD among 38 biallelic markers with minor allele frequencies >.1, since these are most comparable to the common disease-susceptibility polymorphisms that association studies aim to detect. The markers come from three chromosomal regions-1,335 kb on chromosome 13q12-13, 380 kb on chromosome 19q13.2, and 120 kb on chromosome 22q13.3-which have been extensively mapped. These markers were examined in approximately 1,600 individuals from four populations, all of European origin but with different demographic histories; Afrikaners, Ashkenazim, Finns, and East Anglian British. There are few differences, either in allele frequencies or in LD, among the populations studied. A similar inverse relationship was found between LD and distance in each genomic region and in each population. Mean D' is.68 for marker pairs <5 kb apart and is.24 for pairs separated by 10-20 kb, and the level of LD is not different from that seen in unlinked marker pairs separated by >500 kb. However, only 50% of marker pairs at distances <5 kb display sufficient LD (delta>.3) to be useful in association studies. Results of the present study, if representative of the whole genome, suggest that a whole-genome scan searching for common disease-susceptibility alleles would require markers spaced < or = 5 kb apart.

Published
2000
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16. Two amino acid substitutions in apolipoprotein B are in complete allelic association with the antigen group (x/y) polymorphism: evidence for little recombination in the 3' end of the human gene.

Author

Dunning AM, Renges HH, Xu CF, Peacock R, Brasseur R, Laxer G, Tikkanen MJ, Bütler R, Saha N, and Hamsten A

Subjects
Adult, Alleles, Base Sequence, Biological Evolution, Blotting, Southern, Cholesterol blood, DNA genetics, Epitopes genetics, Female, Genetics, Population, Genotype, Homozygote, Humans, Linkage Disequilibrium, Male, Middle Aged, Molecular Sequence Data, Mutation, Restriction Mapping, Amino Acids genetics, Antigens genetics, Apolipoproteins B genetics, Polymorphism, Genetic, Recombination, Genetic
Abstract

We report the identification of an A-to-G base change, in exon 29 of the apolipoprotein B (apo B) gene, that results in the substitution of serine for asparagine at residue 4311 of mature apo B100. In a recent publication, Huang et al. have reported a C-to-T base change in exon 26 that causes the substitution of leucine for proline at residue 2712 of apo B. We have found complete linkage disequilibrium between the alleles at both these sites and an immunochemical polymorphism of LDL designated antigen group (x/y) (Ag(x/y)) in a sample of 118 Finnish individuals. This implies that either one of these substitutions--or both of them combined--could be the molecular basis of the Ag(x/y) antigenic determinants, with the allele encoding serine4311 plus leucine2712 representing the Ag(x) epitope, and that encoding asparagine4311 plus proline2712 the Ag(y) epitope. In a sample of 90 healthy Swedish individuals the Leu2712/Ser4311 allele is associated both with reduced serum levels of LDL-cholesterol and apo B and with raised levels of HDL. However, these differences are of smaller effect than those associated with the XbaI RFLP of the apo B gene in this sample. We have also genotyped 523 individuals from European, Asian, Chinese, and Afro-Caribbean populations and have found complete association between the sites encoding residues 2712 and 4311 in all of these samples, although there are large allele frequency differences between these populations. In addition, there is strong linkage disequilibrium with allelic association between the alleles of these sites and those of the XbaI RFLP in all the populations examined. Taken together, these data suggest that, since the divergence of the major ethnic groups, there has been little or no recombination in the 3' end of the human apo B gene.

Published
1992

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