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6. SOME PROPERTIES OF PAIR OF n-ISOCLINISM INDUCTION.

Author

SAJEDI, M. and DARABI, H.

Subjects
SUBGROUP growth, GROUP theory, MATHEMATICAL induction, INVARIANT sets, MATHEMATICAL proofs
Abstract

Let (G;M) be a pair of groups, in whichM is a normal subgroup of a group G:We study some properties of n-isoclinism of pair of groups. In fact, we show that the subgroups and quotient groups of two n-isoclinism pair of groups are m-isoclinic for all m ≤ n: Moreover, the properties of π-pair and supersolvable pair of groups which are invariant under n-isoclinism has be studied. [ABSTRACT FROM AUTHOR]

Published
2023

7. Probability of Normality of Chains in Finite Groups.

Author

Sajedi, M., Moghaddam, M. R. R., and Darabi, H.

Subjects
FINITE groups, PROBABILITY theory, MARKOV processes, QUATERNIONS, MODULAR groups
Abstract

In this paper we introduce the concept of probability of normality of chains in finite groups. For any normal subgroup N of a finite group G, the relation between the probability of normality of chains of G and of its factor group G=N are obtained. Finally, we give explicit formulas for such probability of dihedral groups D2n, quasi-dihedral groups QD2n, generalized quaternion groups Q2n, and the modular p-groups Mpn. [ABSTRACT FROM AUTHOR]

Published
2023

9. Machine learning techniques for urban flood risk assessment

Author

Darabi, H. (Hamid), Haghighi, A. (Ali Torabi), and Kløve, B. (Bjørn)

Subjects
NN-SGW malli, NN-SGW model, confusion matrix, flood risk mapping, tulvariskien kartoitus, flood inventory data, sekaannusmatriisi, tulvien data-aineistot
Abstract

Floods can cause severe damage in urban environments. In regions lacking hydrological and hydraulic data, spatial urban flood modeling and mapping can enable city authorities to predict the intensity and spatial distribution of floods. These predictions can then be used to develop effective flood prevention and management plans. In this doctoral thesis, flood inventory data for Mazandaran, Iran were prepared based on historical and field survey data from the Sari and Amol municipalities and the regional water company. Flood risk maps were produced using several machine learning (ML) algorithms: GARP, QUEST, RF, j48DT, CART, LMT, ANN-SGW, SVM, MAXENT, BRT, MARS, GLM, GAM, Ensemble, MLPNN, and MultiB-MLPNN models. The flood influencing factors used in modeling were precipitation, slope, curve number, distance to river, distance to channel, depth to groundwater, land use, and elevation. Two equal sets of points were identified randomly for both categories of flooded and non-flooded areas. Therefore, 113 (for Sari city) and 118 (for Amol city) locations for each category were identified. Each set is divided into training (70%) and testing (30%) groups. The flood locations were assigned a value of 1, and non-flood locations were assigned a value of 0. Different conditioning factors, including urban density, quality of buildings, age of buildings, population density, and socio-economic conditions were considered to analyze urban flood vulnerability. Several confusion matrix criteria were applied to evaluate the accuracy of the ML algorithms. The results demonstrated that the ANN-SGW (as the optimized model), GARP (as the standalone model), Ensemble (BRT, MARS, GLM, and GAM), and MultiB-MLPNN models (as the hybridized model) had the highest performance accuracy, with area under the curve (AUC) values of 0.963, 0.935, 0.925, and 0.847 respectively. The results also indicated that distance to channel played a major role in flood hazard determination, whereas population density was the most important factor in terms of urban flood vulnerability. These findings demonstrate that machine learning models can support flood risk mapping, especially in areas where detailed hydraulic and hydrological data are not available. Tiivistelmä Tulvat voivat aiheuttaa vakavia vahinkoja kaupunkiympäristössä. Alueilla, joista hydrologisia ja hydraulisia tietoja ei ole kattavasti saatavilla, kaupunkitulvien alueellinen mallinnus ja kartoitus avaavat mahdollisuuden viranomaisille arvioida tulvien alueellista jakautumista ja voimakkuutta. Mallinnus auttaa päätöksentekijöitä kehittämään toimivia tulvien ehkäisy- ja hallintasuunnitelmia. Tässä tutkimuksessa tulvainventointitiedot laadittiin Sarin ja Amolin kuntien sekä Iranin Mazandaranin vesiyhtiön historiallisten ja kenttätutkimusten tietojen perusteella. Tulvariskikarttoja tuotettiin useilla koneoppimisalgoritmeillä: GARP, QUEST, RF, j48DT, CART, LMT, ANN-SGW, SVM, MAXENT, BRT, MARS, GLM, GAM, Ensemble, MLPNN, ja MultiB-MLPNN mallit. Mallinnuksessa käytettyjä tulviin vaikuttavia tekijöitä olivat sadanta, maanpinnan kaltevuus, käyrän numero, etäisyys jokeen, etäisyys kanavaan, etäisyys pohjaveden pintaan, maankäyttö ja maanpinnan korkeus. Kaksi samanlaista pistejoukkoa tunnistettiin satunnaisesti sekä tulvivalla että tulvattomalla alueella ja siksi kullekin luokalle tunnistettiin 113 (Sarin kaupunki) ja 118 (Amolin kaupunki) sijaintia. Jokainen sarja on jaettu koulutusryhmiin (70 %) ja testausryhmiin (30 %). Tulvapaikoille määritettiin arvo 1 ja tulvattomille arvo 0. Kaupunkien tulvahaavoittuvuuden analysoinnissa arvioitiin erilaisia tekijöitä, kuten rakennustiheys, rakennusten laatu, rakennusten ikä, väestötiheys ja sosioekonomiset olosuhteet. ML-algoritmien tarkkuuden arvioimiseksi käytettiin useita sekaannusmatriisikriteerejä. Tulokset osoittivat, että ANN-SGW (optimoitu malli), GARP (erillisenä mallina), yhdistelmä-ensemble (BRT, MARS, GLM ja GAM) ja MultiB-MLPNN-mallit (hybridimallina) tuottivat muita paremman suorituksen tarkkuuden, AUC=0.963, AUC=0.935, AUC=0.925 ja AUC=0.847, edellä mainitussa järjestyksessä. Tulokset osoittivat myös, että etäisyys kanavaan oli tärkeässä asemassa tulvariskien määrittämisessä, kun taas väestötiheys oli haavoittuvuuden kannalta tärkein tekijä. Nämä havainnot osoittavat, että koneoppimismallit voivat auttaa tulvariskikartoituksessa erityisesti alueilla, joilla yksityiskohtaisia hydrauliikka- ja hydrologisia tietoja ei ole saatavilla.

Published
2022

10. A hybridized model based on neural network and swarm intelligence-grey wolf algorithm for spatial prediction of urban flood-inundation

Author

Darabi, H. (Hamid), Torabi Haghighi, A. (Ali), Rahmati, O. (Omid), Jalali Shahrood, A. (Abolfazl), Rouzbeh, S. (Sajad), Pradhan, B. (Biswajeet), and Tien Bui, D. (Dieu)

Subjects
Confusion matrix, NN-SGW model, Environmental Engineering, Flood inundation, Flood inventory, GIS
Abstract

In regions with lack of hydrological and hydraulic data, a spatial flood modeling and mapping is an opportunity for the urban authorities to predict the spatial distribution and the intensity of the flooding. It helps decision-makers to develop effective flood prevention and management plans. In this study, flood inventory data were prepared based on the historical and field surveys data by Sari municipality and regional water company of Mazandaran, Iran. The collected flood data accompanied with different variables (digital elevation model and slope have been considered as topographic variables, land use/land cover, precipitation, curve number, distance to river, distance to channel and depth to groundwater as environmental variables) were applied to novel hybridized model based on neural network and swarm intelligence-grey wolf algorithm (NN-SGW) to map flood-inundation. Several confusion matrix criteria were used for accuracy evaluation by cutoff-dependent and independent metrics (e.g., efficiency (E), positive predictive value (PPV), negative predictive value (NPV), area under the receiver operating characteristic curve (AUC)). The accuracy of the flood inundation map produced by the NN-SGW model was compared with that of maps produced by four state-of-the-art benchmark models: random forest (RF), logistic model tree (LMT), classification and regression trees (CART), and J48 decision tree (J48DT). The NN-SGW model outperformed all benchmark models in both training (E = 90.5%, PPV = 93.7%, NPV = 87.3%, AUC = 96.3%) and validation (E = 79.4%, PPV = 85.3%, NPV = 73.5%, AUC = 88.2%). As the NN-SGW model produced the most accurate flood-inundation map, it can be employed for robust flood contingency planning. Based on the obtained results from NN-SGW model, distance from channel, distance from river, and depth to groundwater were identified as the most important variables for spatial prediction of urban flood inundation. This work can serve as a basis for future studies seeking to predict flood susceptibility in urban areas using hybridized machine learning (ML) models and can also be applied in other urban areas where flood inundation presents a pressing challenge, and there are some problems regarding required model and availability of input data.

Published
2021

12. Variation in physical characteristics of rainfall in Iran, determined using daily rainfall concentration index and monthly rainfall percentage index

Author

Kaboli, S. (Sadegh), Hekmatzadeh, A. A. (Ali Akbar), Darabi, H. (Hamid), and Haghighi, A. T. (Ali Torabi)

Subjects
education, geographic locations
Abstract

Variations in rainfall characteristics play a key role in available water resources for a country. In this study, spatial and temporal variations in rainfall in Iran were determined using the daily rainfall concentration index (DRCI) and monthly rainfall percentage index (MRPI), based on 30-year (1987–2016) daily precipitation records from 80 meteorological stations throughout Iran. The results showed that MRPI differed between locations within Iran, with increasing or decreasing trends observed in different areas. The highest significant decreasing trend in MRPI (3–7% per decade) was found for March rainfall in western Iran, and the highest increasing trend in MRPI (3–7% per decade) for November rainfall in eastern and southern Iran. The DRCI values obtained varied from 0.57 to 0.71, indicating moderate and high rainfall concentrations, with the highest DRCI values in coastal zones of Iran near the Caspian Sea and the Persian Gulf. Trend analysis showed increasing trends in DRCI values at 80% of meteorological stations, and these trends were significant at 37% of those stations.

Published
2021

13. Toward the development of deep-learning analyses for snow avalanche releases in mountain regions

Author

Chen, Y. (Yunzhi), Chen, W. (Wei), Rahmati, O. (Omid), Falah, F. (Fatemeh), Kulakowski, D. (Dominik), Lee, S. (Saro), Rezaie, F. (Fatemeh), Panahi, M. (Mahdi), Bahmani, A. (Aref), Darabi, H. (Hamid), Torabi Haghighi, A. (Ali), and Bian, H. (Huiyuan)

Subjects
snow avalanche, natural disasters, GIS, artificial intelligence
Abstract

Snow avalanches impose a considerable threat to infrastructure and human safety in snow bound mountain areas. Nevertheless, the spatial prediction of snow avalanches has received little research attention in many vulnerable parts of the world, particularly in developing countries. The present study investigates the applicability of a stand-alone convolutional neural network (CNN) model, as a deep-learning approach, along with two metaheuristic algorithms including grey wolf optimization (CNN-GWO) and imperialist competitive algorithm (CNN-ICA) in snow avalanche modeling in the Darvan watershed, Iran. The analysis was based on thirteen potential drivers of avalanche occurrence and an inventory map of previously documented avalanche occurrences. The efficiency of models’ performance was evaluated by Area Under the Receiver Operating Characteristic curve (AUC) and the Root Mean Square Error (RMSE). The CNN-ICA model yielded the highest accuracy in both training (AUC= 0.982, RMSE =0.067) and validation (AUC= 0.972, RMSE =0.125) steps, followed by the CNN-GWO model (AUC of 0.975 for training, RMSE of 0.18 for training, AUC of 0.968 for validation, RMSE of 0.157 for validation). However, the standalone CNN model showed lower goodness-of-fit (AUC= 0.864, RMSE =0.22) and predictive performance (AUC= 0.811, RMSE =0.330). The approach utilized in this study is broadly applicable for identifying areas where avalanche hazard is likely to be high and where mitigation measures or corresponding land use planning should be prioritized.

Published
2021

14. Analysis and optimization of direct-conversion receivers with 25% duty-cycle current-driven passive mixers

Author

Mirzaei, A., Darabi, H., Leete, J.C., and Yuyu Chang

Subjects
Electric current converters -- Design and construction, Impedance (Electricity) -- Measurement, Integrated circuits -- Design and construction, Semiconductor chips -- Design and construction, Noise control -- Methods, Electric current converter, Standard IC, Business, Computers and office automation industries, Electronics, Electronics and electrical industries
Published
2010

15. TET:an automated tool for evaluating suitable check-dam sites based on sediment trapping efficiency

Author

Rahmati, O. (Omid), Ghasemieh, H. (Hoda), Samadi, M. (Mahmood), Kalantari, Z. (Zahra), Tiefenbacher, J. P. (John P.), Nalivan, O. A. (Omid Asadi), Cerdà, A. (Artemi), Ghiasi, S. S. (Seid Saeid), Darabi, H. (Hamid), Torabi Haghighi, A. (Ali), and Tien Bui, D. (Dieu)

Subjects
Trap efficiency, Water quality, Sediment, Python language, GIS, Watershed management
Abstract

Sediment control is important for supplying clean water. Although check dams control sediment yield, site selection for check dams based on the sediment trapping efficiency (TE) is often complex and time-consuming. Currently, a multi-step trial-and-error process is used to find the optimal sediment TE for check dam construction, which limits this approach in practice. To cope with this challenge, we developed a user-friendly, cost- and time-efficient geographic information system (GIS)-based tool, the trap efficiency tool (TET), in the Python programming language. We applied the tool to two watersheds, the Hableh-Rud and the Poldokhtar, in Iran. To identify suitable sites for check dams, four scenarios (S1: TE ≥ 60%, S2: TE ≥ 70%, S3: TE ≥ 80%, S4: TE ≥ 90%) were tested. TET identified 189, 117, 96, and 77 suitable sites for building check dams in S1, S2, S3, and S4, respectively, in the Hableh-Rud watershed, and 346, 204, 156, and 60 sites in S1, S2, S3, and S4, respectively, in the Poldokhtar watershed. Evaluation of 136 existing check dams in the Hableh-Rud watershed indicated that only 10% and 5% were well-located and these were in the TE classes of 80–90% and ≥90%, respectively. In the Poldokhtar watershed, only 11% and 8% of the 207 existing check dams fell into TE classes 80–90% and ≥90%, respectively. Thus, the conventional approach for locating suitable sites at which check dams should be constructed is not effective at reaching suitable sediment control efficiency. Importantly, TET provides valuable insights for site selection of check dams and can help decision makers avoid monetary losses incurred by inefficient check-dam performance.

Published
2020

16. RiMARS:an automated river morphodynamics analysis method based on remote sensing multispectral datasets

Author

Shahrood, A. J. (Abolfazl Jalali), Menberu, M. W. (Meseret Walle), Darabi, H. (Hamid), Rahmati, O. (Omid), Rossi, P. M. (Pekka M.), Kløve, B. (Bjørn), and Haghighi, A. T. (Ali Torabi)

Subjects
Sediments, MNDWI, Sinuosity index, RiMARS, River migration, Environmental monitoring, Iran, Landsat, Multispectral image
Abstract

Assessment and monitoring of river morphology own an important role in river engineering; since, changes in river morphology including erosion and sedimentation affect river cross-sections and flow processes. An approach for River Morphodynamics Analysis based on Remote Sensing (RiMARS) was developed and tested on the case of Mollasadra dam construction on the Kor River, Iran. Landsat multispectral images obtained from the open USGS dataset are used to extract river morphology dynamics by the Modified Normalized Difference Water Index (MNDWI). RiMARS comes with a river extraction module which is independent of threshold segmentation methods to produce binary-level images. In addition, RiMARS is equipped with developed indices for assessing the morphological alterations. Five characteristics of river morphology (spatiotemporal Sinuosity Index (SI), Absolute Centerline Migration (ACM), Rate of Centerline Migration (RCM), River Linear Pattern (RLP), and Meander Migration Index (MMI)), are applied to quantify river morphology changes. The results indicated that the Kor River centerline underwent average annual migration of 40 cm to the southwest during 1993–2003 (pre-construction impact), 20 cm to the northeast during 2003–2011, and 40 cm to the south-west during 2011–2017 (post-construction impact). Spatially, as the Kor River runs towards the Doroudzan dam, changes in river morphology have increased from upstream to downstream; particularly evident where the river flows in a plain instead of the valley. Based on SI values, there was a 5% change in the straight sinuosity class in the pre-construction period, but an 18% decrease in the straight class during the post-construction period. Here we demonstrate the application of RiMARS in assessing the impact of dam construction on morphometric processes in Kor River, but it can be used to assess other riverine changes, including tracking the unauthorized water consumption using diverted canals. RiMARS can be applied on multispectral images.

Published
2020

17. Flash-flood hazard assessment using ensembles and Bayesian-based machine learning models:application of the simulated annealing feature selection method

Author

Hosseini, F. S. (Farzaneh Sajedi), Choubin, B. (Bahram), Mosavi, A. (Amir), Nabipour, N. (Narjes), Shamshirband, S. (Shahaboddin), Darabi, H. (Hamid), and Haghighi, A. T. (Ali Torabi)

Subjects
flash-flood, hazard, ensemble machine learning, simulated annealing, Bayesian
Abstract

Flash-floods are increasingly recognized as a frequent natural hazard worldwide. Iran has been among the most devastated regions affected by the major floods. While the temporal flash-flood forecasting models are mainly developed for warning systems, the models for assessing hazardous areas can greatly contribute to adaptation and mitigation policy-making and disaster risk reduction. Former researches in the flash-flood hazard mapping have heightened the urge for the advancement of more accurate models. Thus, the current research proposes the state-of-the-art ensemble models of boosted generalized linear model (GLMBoost) and random forest (RF), and Bayesian generalized linear model (BayesGLM) methods for higher performance modeling. Furthermore, a pre-processing method, namely simulated annealing (SA), is used to eliminate redundant variables from the modeling process. Results of the modeling based on the hit and miss analysis indicates high performance for both models (accuracy= 90−92%, Kappa= 79−84%, Success ratio= 94−96%, Threat score= 80−84%, and Heidke skill score= 79−84%). The variables of distance from the stream, vegetation, drainage density, land use, and elevation have shown more contribution among others for modeling the flash-flood. The results of this study can significantly facilitate mapping the hazardous areas and further assist watershed managers to control and remediate induced damages of flood in the data-scarce regions.

Published
2019

18. Evidence that breast cancer risk at the 2q35 locus is mediated through IGFBP5 regulation (vol 5, 4999, 2014)

Author

Ghoussaini, M., Edwards, S.L., Michailidou, K., Nord, S., Lari, R.C.S., Desai, K., Kar, S., Hillman, K.M., Kaufmann, S., Glubb, D.M., Beesley, J., Dennis, J., Bolla, M.K., Wang, Q., Dicks, E., Guo, Q., Schmidt, M.K., Shah, M., Luben, R., Brown, J., Czene, K., Darabi, H., Eriksson, M., Klevebring, D., Bojesen, S.E., Nordestgaard, B.G., Nielsen, S.F., Flyger, H., Lambrechts, D., Thienpont, B., Neven, P., Wildiers, H., Broeks, A., Van't Veer, L.J., Rutgers, E.J.T., Couch, F.J., Olson, J.E., Hallberg, E., Vachon, C., Chang-Claude, J., Rudolph, A., Seibold, P., Flesch-Janys, D., Peto, J., dos-Santos-Silva, I., Gibson, L., Nevanlinna, H., Muranen, T.A., Aittomaki, K., Blomqvist, C., Hall, P., Li, J.M., Liu, J.J., Humphreys, K., Kang, D., Choi, J.Y., Park, S.K., Noh, D.Y., Matsuo, K., Ito, H., Iwata, H., Yatabe, Y., Guenel, P., Truong, T., Menegaux, F., Sanchez, M., Burwinkel, B., Marme, F., Schneeweiss, A., Sohn, C., Wu, A.H., Tseng, C.C., Berg, D. van den, Stram, D.O., Benitez, J., Zamora, M., Perez, J.I.A., Menendez, P., Shu, X.O., Lu, W., Gao, Y.T., Cai, Q.Y., Cox, A., Cross, S.S., Reed, M.W.R., Andrulis, I.L., Knight, J.A., Glendon, G., Tchatchou, S., Sawyer, E.J., Tomlinson, I., Kerin, M.J., Miller, N., Haiman, C.A., Henderson, B.E., Schumacher, F., Marchand, L. le, Lindblom, A., Margolin, S., Teo, S.H., Yip, C.H., Lee, D.S.C., Wong, T.Y., Hooning, M.J., Martens, J.W.M., Collee, J.M., Deurzen, C.H.M. van, Hopper, J.L., Southey, M.C., Tsimiklis, H., Kapuscinski, M.K., Shen, C.Y., Wu, P.E., Yu, J.C., Chen, S.T., Alnaes, G.G., Borresen-Dale, A.L., Giles, G.G., Milne, R.L., McLean, C., Muir, K., Lophatananon, A., Stewart-Brown, S., Siriwanarangsan, P., Hartman, M., Miao, H., Buhari, S.A.B.S., Teo, Y.Y., Fasching, P.A., Haeberle, L., Ekici, A.B., Beckmann, M.W., Brenner, H., Dieffenbach, A.K., Arndt, V., Stegmaier, C., Swerdlow, A., Ashworth, A., Orr, N., Schoemaker, M.J., Garcia-Closas, M., Figueroa, J., Chanock, S.J., Lissowska, J., Simard, J., Goldberg, M.S., Labreche, F., Dumont, M., Winqvist, R., Pylkas, K., Jukkola-Vuorinen, A., Brauch, H., Bruning, T., Koto, Y.D., Radice, P., Peterlongo, P., Bonanni, B., Volorio, S., Dork, T., Bogdanova, N.V., Helbig, S., Mannermaa, A., Kataja, V., Kosma, V.M., Hartikainen, J.M., Devilee, P., Tollenaar, R.A.E.M., Seynaeve, C., Asperen, C.J. van, Jakubowska, A., Lubinski, J., Jaworska-Bieniek, K., Durda, K., Slager, S., Toland, A.E., Ambrosone, C.B., Yannoukakos, D., Sangrajrang, S., Gaborieau, V., Brennan, P., Mckay, J., Hamann, U., Torres, D., Zheng, W., Long, J.R., Anton-Culver, H., Neuhausen, S.L., Luccarini, C., Baynes, C., Ahmed, S., Maranian, M., Healey, C.S., Gonzalez-Neira, A., Pita, G., Alonso, M.R., Alvarez, N., Herrero, D., Tessier, D.C., Vincent, D., Bacot, F., Santiago, I. de, Carroll, J., Caldas, C., Brown, M.A., Lupien, M., Kristensen, V.N., Pharoah, P.D.P., Chenevix-Trench, G., French, J.D., Easton, D.F., Dunning, A.M., and Australian Ovarian Canc Management

Published
2018

19. On classification of (n+5)-dimensional nilpotent n-Lie algebra of class two

Author

Hoseini, Z., Saeedi, F., and Darabi, H.

Subjects
Rings and Algebras (math.RA), FOS: Mathematics, Group Theory (math.GR), Mathematics - Rings and Algebras, Mathematics - Group Theory
Abstract

In this paper, we classify (n+5)-dimensional nilpotent n-Lie algebras of class two over the arbitrary field, when $n\ge 3$.

Published
2018

20. Use of remote sensing to analyse peatland changes afterdrainage for peat extraction

Author

Haghighi, A. T. (Ali Torabi), Menberu, M. W. (Meseret Walle), Darabi, H. (Hamid), Akanegbu, J. (Justice), and Kløve, B. (Bjørn)

Subjects
disturbance, remote sensing, NDVI, land use, peatlands, wetlands
Abstract

Large‐scale peat extraction, in Finland and elsewhere, typically takes place on rather small extraction sites but has major impacts on surrounding aquatic and terrestrial ecosystems. The environmental conditions prior to drainage (baseline conditions) must be quantified in a statutory environmental impact assessment (EIA), but this is generally difficult due to lack of historical data. In this study, we developed and tested a method for EIA based on a reference area approach and remote sensing. The method calculates the normalized difference vegetation index in preextraction and postextraction periods using Landsat images of affected areas and reference surrounding areas. In a case study, we applied the method to assess changes after peat extraction at a site in northern Finland. The peat extraction area showed significant transformation from peatland vegetation to bare soil. Adjacent areas downstream and upstream were also affected by extraction. These results indicate that our method is a useful tool for EIA of peatland drainage.

Published
2018

21. Body mass index and breast cancer survival:a Mendelian randomization analysis

Author

Guo, Q. (Qi), Burgess, S. (Stephen), Turman, C. (Constance), Bolla, M. K. (Manjeet K.), Wang, Q. (Qin), Lush, M. (Michael), Abraham, J. (Jean), Aittomaki, K. (Kristiina), Andrulis, I. L. (Irene L.), Apicella, C. (Carmel), Arndt, V. (Volker), Barrdahl, M. (Myrto), Benitez, J. (Javier), Berg, C. D. (Christine D.), Blomqvist, C. (Carl), Bojesen, S. E. (Stig E.), Bonanni, B. (Bernardo), Brand, J. S. (Judith S.), Brenner, H. (Hermann), Broeks, A. (Annegien), Burwinkel, B. (Barbara), Caldas, C. (Carlos), Campa, D. (Daniele), Canzian, F. (Federico), Chang-Claude, J. (Jenny), Chanock, S. J. (Stephen J.), Chin, S.-F. (Suet-Feung), Couch, F. J. (Fergus J.), Cox, A. (Angela), Cross, S. S. (Simon S.), Cybulski, C. (Cezary), Czene, K. (Kamila), Darabi, H. (Hatef), Devilee, P. (Peter), Diver, W. R. (W. Ryan), Dunning, A. M. (Alison M.), Earl, H. M. (Helena M.), Eccles, D. M. (Diana M.), Ekici, A. B. (Arif B.), Eriksson, M. (Mikael), Evans, D. G. (D. Gareth), Fasching, P. A. (Peter A.), Figueroa, J. (Jonine), Flesch-Janys, D. (Dieter), Flyger, H. (Henrik), Gapstur, S. M. (Susan M.), Gaudet, M. M. (Mia M.), Giles, G. G. (Graham G.), Glendon, G. (Gord), Grip, M. (Mervi), Gronwald, J. (Jacek), Haeberle, L. (Lothar), Haiman, C. A. (Christopher A.), Hall, P. (Per), Hamann, U. (Ute), Hankinson, S. (Susan), Hartikainen, J. M. (Jaana M.), Hein, A. (Alexander), Hiller, L. (Louise), Hogervorst, F. B. (Frans B.), Holleczek, B. (Bernd), Hooning, M. J. (Maartje J.), Hoover, R. N. (Robert N.), Humphreys, K. (Keith), Hunter, D. J. (David J.), Husing, A. (Anika), Jakubowska, A. (Anna), Jukkola-Vuorinen, A. (Arja), Kaaks, R. (Rudolf), Kabisch, M. (Maria), Kataja, V. (Vesa), Knight, J. A. (Julia A.), Koppert, L. B. (Linetta B.), Kosma, V.-M. (Veli-Matti), Kristensen, V. N. (Vessela N.), Lambrechts, D. (Diether), Le Marchand, L. (Loic), Li, J. (Jingmei), Lindblom, A. (Annika), Lindstrom, S. (Sara), Lissowska, J. (Jolanta), Lubinski, J. (Jan), Machiela, M. J. (Mitchell J.), Mannermaa, A. (Arto), Manoukian, S. (Siranoush), Margolin, S. (Sara), Marme, F. (Federik), Martens, J. W. (John W. M.), McLean, C. (Catriona), Menendez, P. (Primitiva), Milne, R. L. (Roger L.), Mulligan, A. M. (Anna Marie), Muranen, T. A. (Taru A.), Nevanlinna, H. (Heli), Neven, P. (Patrick), Nielsen, S. F. (Sune F.), Nordestgaard, B. G. (Borge G.), Olson, J. E. (Janet E.), Perez, J. I. (Jose I. A.), Peterlongo, P. (Paolo), Phillips, K.-A. (Kelly-Anne), Poole, C. J. (Christopher J.), Pylkas, K. (Katri), Radice, P. (Paolo), Rahman, N. (Nazneen), Rudiger, T. (Thomas), Rudolph, A. (Anja), Sawyer, E. J. (Elinor J.), Schumacher, F. (Fredrick), Seibold, P. (Petra), Seynaeve, C. (Caroline), Shah, M. (Mitul), Smeets, A. (Ann), Southey, M. C. (Melissa C.), Tollenaar, R. A. (Rob A. E. M.), Tomlinson, I. (Ian), Tsimiklis, H. (Helen), Ulmer, H.-U. (Hans-Ulrich), Vachon, C. (Celine), van den Ouweland, A. M. (Ans M. W.), Van't Veer, L. J. (Laura J.), Wildiers, H. (Hans), Willett, W. (Walter), Winqvist, R. (Robert), Zamora, M. P. (M. Pilar), Chenevix-Trench, G. (Georgia), Dork, T. (Thilo), Easton, D. F. (Douglas F.), Garcia-Closas, M. (Montserrat), Kraft, P. (Peter), Hopper, J. L. (John L.), Zheng, W. (Wei), Schmidt, M. K. (Marjanka K.), and Pharoah, P. D. (Paul D. P.)

Subjects
Mendelian randomization, breast cancer survival, body mass index, epidemiology, genetics
Abstract

Background: There is increasing evidence that elevated body mass index (BMI) is associated with reduced survival for women with breast cancer. However, the underlying reasons remain unclear. We conducted a Mendelian randomization analysis to investigate a possible causal role of BMI in survival from breast cancer. Methods: We used individual-level data from six large breast cancer case-cohorts including a total of 36 210 individuals (2475 events) of European ancestry. We created a BMI genetic risk score (GRS) based on genotypes at 94 known BMI-associated genetic variants. Association between the BMI genetic score and breast cancer survival was analysed by Cox regression for each study separately. Study-specific hazard ratios were pooled using fixed-effect meta-analysis. Results: BMI genetic score was found to be associated with reduced breast cancer-specific survival for estrogen receptor (ER)-positive cases [hazard ratio (HR) = 1.11, per one-unit increment of GRS, 95% confidence interval (CI) 1.01–1.22, P = 0.03). We observed no association for ER-negative cases (HR = 1.00, per one-unit increment of GRS, 95% CI 0.89–1.13, P = 0.95). Conclusions: Our findings suggest a causal effect of increased BMI on reduced breast cancer survival for ER-positive breast cancer. There is no evidence of a causal effect of higher BMI on survival for ER-negative breast cancer cases.

Published
2017

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

Author

Ghoussaini, M., French, J.D., Michailidou, K., Nord, S., Beesley, J., Canisus, S., Hillman, K.M., Kaufmann, S., Sivakumaran, H., Marjaneh, M.M., Lee, J.S., Dennis, J., Bolla, M.K., Wang, Q., Dicks, E., Milne, R.L., Hopper, J.L., Southey, M.C., Schmidt, M.K., Broeks, A., Muir, K., Lophatananon, A., Fasching, P.A., Beckmann, M.W., Fletcher, O., Johnson, N., Sawyer, E.J., Tomlinson, I., Burwinkel, B., Marme, F., Guenel, P., Truong, T., Bojesen, S.E., Flyger, H., Benitez, J., Gonzalez-Neira, A., Alonso, R., Pita, G., Neuhausen, S.L., Anton-Culver, H., Brenner, H., Arndt, V., Meindl, A., Schmutzler, R.K., Brauch, H., Hamann, U., Tessier, D.C., Vincent, D., Nevanlinna, H., Khan, S., Matsuo, K., Ito, H., Dork, T., Bogdanova, N.V., Lindblom, A., Margolin, S., Mannermaa, A., Kosma, V.M., Wu, A.H., Berg, D. van den, Lambrechts, D., Floris, G., Chang-Claude, J., Rudolph, A., Radice, P., Barile, M., Couch, F.J., Hallberg, E., Giles, G.G., Haiman, C.A., Marchand, L. le, Goldberg, M.S., Teo, S.H., Yip, C.H., Borresen-Dale, A.L., Zheng, W., Cai, Q.Y., Winqvist, R., Pylkas, K., Andrulis, I.L., Devilee, P., Tollenaar, R.A.E.M., Garcia-Closas, M., Figueroa, J., Hall, P., Czene, K., Brand, J.S., Darabi, H., Eriksson, M., Hooning, M.J., Koppert, L.B., Li, J.M., Shu, X.O., Zheng, Y., Cox, A., Cross, S.S., Shah, M., Rhenius, V., Choi, J.Y., Kang, D., Hartman, M., Chia, K.S., Kabisch, M., Torres, D., Luccarini, C., Conroy, D.M., Jakubowska, A., Lubinski, J., Sangrajrang, S., Brennan, P., Olswold, C., Slager, S., Shen, C.Y., Hou, M.F., Swerdlow, A., Schoemaker, M.J., Simard, J., Pharoah, P.D.P., Kristensen, V., Chenevix-Trench, G., Easton, D.F., Dunning, A.M., Edwards, S.L., kConFab AOCS, NBCS Collaborators, Dennis, Joe [0000-0003-4591-1214], Wang, Jean [0000-0002-9139-0627], Dicks, Ed [0000-0002-0617-0401], Rhenius, Valerie [0000-0003-4215-3235], Pharoah, Paul [0000-0001-8494-732X], Easton, Douglas [0000-0003-2444-3247], Dunning, Alison [0000-0001-6651-7166], and Apollo - University of Cambridge Repository

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

Published
2016

23. Evidence that the 5p12 variant rs10941679 confers susceptibility to estrogen receptor positive breast cancer through FGF10 and MRPS30 regulation

Author

Ghoussaini, M, French, J.D., Michailidou, K., Nord, S., Beesley, J., Canisus, S., Hillman, K.M., Kaufmann, S., Sivakumaran, H., Marjaneh, M.M., Lee, J.S., Dennis, J., Bolla, M.K., Wang, Q., Dicks, E., Milne, R.L., Hopper, J.L., Southey, M.C., Schmidt, M.K., Broeks, A., Muir, K., Lophatananon, A, Fasching, P.A., Beckmann, M.W., Fletcher, O., Johnson, N., Sawyer, E.J., Tomlinson, I., Burwinkel, B., Marme, F., Guenel, P., Truong, T., Bojesen, S.E., Flyger, H., Benitez, J., González-Neira, A., Alonson, M.R., Pita, G., Neuhausen, S.L., Anton-Culver, H., Brenner, H., Arndt, V., Meindl, A., Schmutzler, R.K., Brauch, H., Hamann, U., Tessier, D.C., Vincent, D., Nevanlinna, H., Khan, S., Matsuo, K., Ito, H., Dörk, T., Bogdanova, N.V., Lindblom, A., Margolin, S., Mannermaa, A., Kosma, V-M., kConFab/AOCS Investigators, Wu, A.H., Van Den Berg, D., Lambrechts, D., Floris, G., Chang-Claude, J., Rudolph, A., Radice, P., Barile, M., Couch, F.J., Hallberg, E., Giles, G.G., Haiman, C.A., Le Marchand, L., Goldberg, M.S., Teo, S.H., Yip, C.H., Borresen-Dale, A-L., NBCS Collaborators, Zheng, W., Cai, Q., Winqvist, R., Pylkäs, K., Andrulis, I.L., Devilee, P., Tollenaar, R.A.E.M., García-Closas, M., Figueroa, J., Hall, P., Czene, K, Brand, J.S., Darabi, H, Eriksson, M., Hooning, M.J., Koppert, L.B., Jingmei, L., Shu, X-O., Zheng, Y., Cox, A, Cross, S.S., Shah, M., Rhenius, V., Choi, J-Y., Kang, D., Hartman, M., Chia, K.S., Kabisch, M., Torres, D., Luccarini, C., Conroy, D.M, Jakubowska, A., Libinski, J., Sangrajrang, S., Brennan, P., Olswold, C., Slager, S., Shen, C-Y., Hou, M-F., Swerdlow, A., Schoemaker, M.J., Simard, J., Pharoah, P.D.P, Kristensen, V., Chenevix-Trench, G., Easton, D.F., Dunning, A.M., and Edwards, S.L.

Abstract

Genome-wide association studies (GWAS) 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). Using data for 3,365 genotyped and imputed single nucleotide polymorphisms (SNPs) across a 1Mb (positions 44394495-45364167; NCBI build 37) panel 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=8.35x10-30). 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=1.44E-12); and a single signal 3 SNP (rs200229088: per-t allele OR ER+=1.12; 95% CI 1.09-1.15; P-conditional=1.12E-05). Expression quantitative trait locus analysis in normal breast tissues and breast tumors showed 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 over-expressed in ~10% of human breast cancers, while 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.

Published
2016

24. Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer

Author

Shi, J.J., Zhang, Y.F., Zheng, W., Michailidou, K., Ghoussaini, M., Bolla, M.K., Wang, Q., Dennis, J., Lush, M., Milne, R.L., Shu, X.O., Beesley, J., Kar, S., Andrulis, I.L., Anton-Culver, H., Arndt, V., Beckmann, M.W., Zhao, Z.G., Guo, X.Y., Benitez, J., Beeghly-Fadiel, A., Blot, W., Bogdanova, N.V., Bojesen, S.E., Brauch, H., Brenner, H., Brinton, L., Broeks, A., Bruening, T., Burwinkel, B., Cai, H., Canisius, S., Chang-Claude, J., Choi, J.Y., Couch, F.J., Cox, A., Cross, S.S., Czene, K., Darabi, H., Devilee, P., Droit, A., Dork, T., Fasching, P.A., Fletcher, O., Flyger, H., Fostira, F., Gaborieau, V., Garcia-Closas, M., Giles, G.G., Grip, M., Guenel, P., Haiman, C.A., Hamann, U., Hartman, M., Miao, H., Hollestelle, A., Hopper, J.L., Hsiung, C.N., Investigators, K., Ito, H., Jakubowska, A., Johnson, N., Torres, D., Kabisch, M., Kang, D., Khan, S., Knight, J.A., Kosma, V.M., Lambrechts, D., Li, J.M., Lindblom, A., Lophatananon, A., Lubinski, J., Mannermaa, A., Manoukian, S., Marchand, L. le, Margolin, S., Marme, F., Matsuo, K., McLean, C., Meindl, A., Muir, K., Neuhausen, S.L., Nevanlinna, H., Nord, S., Borresen-Dale, A.L., Olson, J.E., Orr, N., Ouweland, A.M.W. van den, Peterlongo, P., Putti, T.C., Rudolph, A., Sangrajrang, S., Sawyer, E.J., Schmidt, M.K., Schmutzler, R.K., Shen, C.Y., Hou, M.F., Shrubsole, M.J., Southey, M.C., Swerdlow, A., Teo, S.H., Thienpont, B., Toland, A.E., Tollenaar, R.A.E.M., Tomlinson, I., Truong, T., Tseng, C.C., Wen, W.Q., Winqvist, R., Wu, A.H., Yip, C.H., Zamora, P.M., Zheng, Y., Floris, G., Cheng, C.Y., Hooning, M.J., Martens, J.W.M., Seynaeve, C., Kristensen, V.N., Hall, P., Pharoah, P.D.P., Simard, J., Chenevix-Trench, G., Dunning, A.M., Antoniou, A.C., Easton, D.F., Cai, Q.Y., Long, J.R., Ghoussaini, Maya [0000-0002-2415-2143], Wang, Jean [0000-0002-9139-0627], Dennis, Joe [0000-0003-4591-1214], Pharoah, Paul [0000-0001-8494-732X], Dunning, Alison [0000-0001-6651-7166], Antoniou, Antonis [0000-0001-9223-3116], Easton, Douglas [0000-0003-2444-3247], and Apollo - University of Cambridge Repository

Subjects
breast cancer, fine-mapping, single nucleotide polymorphism, 8q24, genetic susceptibility
Abstract

Previous genome-wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. A fine-mapping study across 2.06 Mb (chr8:127,561,724-129,624,067, hg19) in 55,540 breast cancer cases and 51,168 controls within the Breast Cancer Association Consortium was conducted. Three additional independent association signals in women of European ancestry, represented by rs35961416 (OR = 0.95, 95% CI = 0.93-0.97, conditional p = 5.8 × 10(-6) ), rs7815245 (OR = 0.94, 95% CI = 0.91-0.96, conditional p = 1.1 × 10(-6) ) and rs2033101 (OR = 1.05, 95% CI = 1.02-1.07, conditional p = 1.1 × 10(-4) ) were found. Integrative analysis using functional genomic data from the Roadmap Epigenomics, the Encyclopedia of DNA Elements project, the Cancer Genome Atlas and other public resources implied that SNPs rs7815245 in Signal 3, and rs1121948 in Signal 5 (in linkage disequilibrium with rs11780156, r(2) = 0.77), were putatively functional variants for two of the five independent association signals. The results highlighted multiple 8q24 variants associated with breast cancer susceptibility in women of European ancestry.

Published
2016

25. Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

Author

Lawrenson, K, Kar, S, McCue, K, Kuchenbaeker, K, Michailidou, K, Tyrer, J, Beesley, J, Ramus, SJ, Li, Q, Delgado, MK, Lee, JM, Aittomäki, K, Andrulis, IL, Anton-Culver, H, Arndt, V, Arun, BK, Arver, B, Bandera, EV, Barile, M, Barkardottir, RB, Barrowdale, D, Beckmann, MW, Benitez, J, Berchuck, A, Bisogna, M, Bjorge, L, Blomqvist, C, Blot, W, Bogdanova, N, Bojesen, A, Bojesen, SE, Bolla, MK, Bonanni, B, Børresen-Dale, AL, Brauch, H, Brennan, P, Brenner, H, Bruinsma, F, Brunet, J, Buhari, SA, Burwinkel, B, Butzow, R, Buys, SS, Cai, Q, Caldes, T, Campbell, I, Canniotto, R, Chang-Claude, J, Chiquette, J, Choi, JY, Claes, KBM, Cook, LS, Cox, A, Cramer, DW, Cross, SS, Cybulski, C, Czene, K, Daly, MB, Damiola, F, Dansonka-Mieszkowska, A, Darabi, H, Dennis, J, Devilee, P, Diez, O, Doherty, JA, Domchek, SM, Dorfling, CM, Dörk, T, Dumont, M, Ehrencrona, H, Ejlertsen, B, Ellis, S, Engel, C, Lee, E, Evans, DG, Fasching, PA, Feliubadalo, L, Figueroa, J, and Flesch-Janys, D

Abstract

© 2016 The Author(s). A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P

Published
2016

26. Identification and characterization of novel associations in the CASP8/ALS2CR12 region on chromosome 2 with breast cancer risk

Author

Lin, W.Y., Camp, N.J., Ghoussaini, M., Beesley, J., Michailidou, K., Hopper, J.L., Apicella, C., Southey, M.C., Stone, J., Schmidt, M.K., Broeks, A., Van't Veer, L.J., Rutgers, E.J.T., Muir, K., Lophatananon, A., Stewart-Brown, S., Siriwanarangsan, P., Fasching, P.A., Haeberle, L., Ekici, A.B., Beckmann, M.W., Peto, J., Dos-Santos-Silva, I., Fletcher, O., Johnson, N., Bolla, M.K., Wang, Q., Dennis, J., Sawyer, E.J., Cheng, T., Tomlinson, I., Kerin, M.J., Miller, N., Marme, F., Surowy, H.M., Burwinkel, B., Guenel, P., Truong, T., Menegaux, F., Mulot, C., Bojesen, S.E., Nordestgaard, B.G., Nielsen, S.F., Flyger, H., Benitez, J., Zamora, M.P., Perez, J.I.A., Menendez, P., Gonzalez-Neira, A., Pita, G., Alonso, M.R., Alvarez, N., Herrera, D., Anton-Culver, H., Brenner, H., Dieffenbach, A.K., Arndt, V., Stegmaier, C., Meindl, A., Lichtner, P., Schmutzler, R.K., Muller-Myhsok, B., Brauch, H., Bruning, T., Ko, Y.D., Tessier, D.C., Vincent, D., Bacot, F., Nevanlinna, H., Aittomaki, K., Blomqvist, C., Khan, S., Matsuo, K., Ito, H., Iwata, H., Horio, A., Bogdanova, N.V., Antonenkova, N.N., Dork, T., Lindblom, A., Margolin, S., Mannermaa, A., Kataja, V., Kosma, V.M., Hartikainen, J.M., Wu, A.H., Tseng, C.C., Berg, D. van den, Stram, D.O., Neven, P., Wauters, E., Wildiers, H., Lambrechts, D., Chang-Claude, J., Rudolph, A., Seibold, P., Flesch-Janys, D., Radice, P., Peterlongo, P., Manoukian, S., Bonanni, B., Couch, F.J., Wang, X.S., Vachon, C., Purrington, K., Giles, G.G., Milne, R.L., Mclean, C., Haiman, C.A., Henderson, B.E., Schumacher, F., Marchand, L. le, Simard, J., Goldberg, M.S., Labreche, F., Dumont, M., Teo, S.H., Yip, C.H., Hassan, N., Vithana, E.N., Kristensen, V., Zheng, W., Deming-Halverson, S., Shrubsole, M.J., Long, J.R., Winqvist, R., Pylkas, K., Jukkola-Vuorinen, A., Kauppila, S., Andrulis, I.L., Knight, J.A., Glendon, G., Tchatchou, S., Devilee, P., Tollenaar, R.A.E.M., Seynaeve, C., Asperen, C.J. van, Garcia-Closas, M., Figueroa, J., Lissowska, J., Brinton, L., Czene, K., Darabi, H., Eriksson, M., Brand, J.S., Hooning, M.J., Hollestelle, A., Ouweland, A.M.W. van den, Jager, A., Li, J.M., Liu, J.J., Humphreys, K., Shu, X.O., Lu, W., Gao, Y.T., Cai, H., Cross, S.S., Reed, M.W.R., Blot, W., Signorello, L.B., Cai, Q.Y., Pharoah, P.D.P., Perkins, B., Shah, M., Blows, F.M., Kang, D., Yoo, K.Y., Noh, D.Y., Hartman, M., Miao, H., Chia, K.S., Putti, T.C., Hamann, U., Luccarini, C., Baynes, C., Ahmed, S., Maranian, M., Healey, C.S., Jakubowska, A., Lubinski, J., Jaworska-Bieniek, K., Durda, K., Sangrajrang, S., Gaborieau, V., Brennan, P., Mckay, J., Slager, S., Toland, A.E., Yannoukakos, D., Shen, C.Y., Hsiung, C.N., Wu, P.E., Ding, S.L., Ashworth, A., Jones, M., Orr, N., Swerdlow, A.J., Tsimiklis, H., Makalic, E., Schmidt, D.F., Bui, Q.M., Chanock, S.J., Hunter, D.J., Hein, R., Dahmen, N., Beckmann, L., Aaltonen, K., Muranen, T.A., Heikkinen, T., Irwanto, A., Rahman, N., Turnbull, C.A., Waisfisz, Q., Meijers-Heijboer, H.E.J., Adank, M.A., Luijt, R.B. van der, Hall, P., Chenevix-Trench, G., Dunning, A., Easton, D.F., Cox, A., GENICA Network, kConFab Investigators, Australian Ovarian Canc Study Grp, Breast Ovarian Canc Susceptibility, Clinical Genetics, Obstetrics & Gynecology, Medical Oncology, Cardiothoracic Surgery, Cancer Center Amsterdam, Amsterdam Reproduction & Development (AR&D), Human Genetics, Human genetics, CCA - Oncogenesis, Ghoussaini, Maya [0000-0002-2415-2143], Wang, Jean [0000-0002-9139-0627], Dennis, Joe [0000-0003-4591-1214], Pharoah, Paul [0000-0001-8494-732X], Dunning, Alison [0000-0001-6651-7166], Easton, Douglas [0000-0003-2444-3247], and Apollo - University of Cambridge Repository

Subjects
Genotyping Techniques, Research Support, U.S. Gov't, P.H.S, CASP8 and FADD-Like Apoptosis Regulating Protein, Genome-wide association study, P.H.S, Medical and Health Sciences, Breast and Ovarian Cancer Susceptibility (BOCS) Study, Medizinische Fakultät, Genetics(clinical), Non-U.S. Gov't, Genetics (clinical), Genetics, Genetics & Heredity, variants, Caspase 8, Research Support, Non-U.S. Gov't, Association Studies Articles, General Medicine, Biological Sciences, ddc, Chromosomes, Human, Pair 2, kConFab Investigators, Female, GENICA Network, Australian Ovarian Cancer Study Group, European Continental Ancestry Group, Non-P.H.S, Single-nucleotide polymorphism, Breast Neoplasms, Biology, Research Support, Polymorphism, Single Nucleotide, White People, N.I.H, Breast cancer, Research Support, N.I.H., Extramural, SDG 3 - Good Health and Well-being, medicine, Journal Article, Humans, Genetic Predisposition to Disease, ddc:610, gene, Genotyping, Molecular Biology, Genetic association, disease, Extramural, Proteins, Odds ratio, medicine.disease, susceptibility loci, Minor allele frequency, Case-Control Studies, genome-wide association, enhancers, U.S. Gov't, casp8, Research Support, U.S. Gov't, Non-P.H.S, Genome-Wide Association Study
Abstract

Previous studies have suggested that polymorphisms in CASP8 on chromosome 2 are associated with breast cancer risk. To clarify the role of CASP8 in breast cancer susceptibility, we carried out dense genotyping of this region in the Breast Cancer Association Consortium (BCAC). Single-nucleotide polymorphisms (SNPs) spanning a 1 Mb region around CASP8 were genotyped in 46 450 breast cancer cases and 42 600 controls of European origin from 41 studies participating in the BCAC as part of a custom genotyping array experiment (iCOGS). Missing genotypes and SNPs were imputed and, after quality exclusions, 501 typed and 1232 imputed SNPs were included in logistic regressionmodels adjusting for study and ancestry principal components. The SNPs retained in the final model were investigated further in data from nine genome-wide association studies (GWAS) comprising in total 10 052 case and 12 575 control subjects. The most significant association signal observed in European subjects was for the imputed intronic SNP rs1830298 in ALS2CR12 (telomeric to CASP8), with per allele odds ratio and 95% confidence interval [OR (95% confidence interval, CI)] for the minor allele of 1.05 (1.03-1.07), P = 1 × 10-5. Three additional independent signals from intronic SNPs were identified, in CASP8 (rs36043647), ALS2CR11 (rs59278883) and CFLAR (rs7558475). The association with rs1830298 was replicated in the imputed results from the combined GWAS (P=3 × 10-6), yielding a combined OR (95% CI) of 1.06 (1.04-1.08), P = 1 × 10-9. Analyses of gene expression associations in peripheral blood and normal breast tissue indicate that CASP8might be the target gene, suggesting amechanism involving apoptosis.

Published
2016

27. Five endometrial cancer risk loci identified through genome-wide association analysis

Author

Cheng, THT, Thompson, DJ, O'Mara, TA, Painter, JN, Glubb, DM, Flach, S, Lewis, A, French, JD, Freeman-Mills, L, Church, D, Gorman, M, Martin, L, National Study of Endometrial Cancer Genetics Group (NSECG), Hodgson, S, Webb, PM, Australian National Endometrial Cancer Study Group (ANECS), Attia, J, Holliday, EG, McEvoy, M, Scott, RJ, Henders, AK, Martin, NG, Montgomery, GW, Nyholt, DR, Ahmed, S, Healey, CS, Shah, M, Dennis, J, Fasching, PA, Beckmann, MW, Hein, A, Ekici, AB, Hall, P, Czene, K, Darabi, H, Li, J, Dörk, T, Dürst, M, Hillemanns, P, Runnebaum, I, Amant, F, Schrauwen, S, Zhao, H, Lambrechts, D, Depreeuw, J, Dowdy, SC, Goode, EL, Fridley, BL, Winham, SJ, Njølstad, TS, Salvesen, HB, Trovik, J, Werner, HMJ, Ashton, K, Otton, G, Proietto, T, Liu, T, Mints, M, Tham, E, RENDOCAS, CHIBCHA Consortium, Li, MJ, Yip, SH, Wang, J, Bolla, MK, Michailidou, K, Wang, Q, Tyrer, JP, Dunlop, M, Houlston, R, Palles, C, Hopper, JL, AOCS Group, Peto, J, Swerdlow, AJ, Burwinkel, B, Brenner, H, Meindl, A, Brauch, H, Lindblom, A, Chang-Claude, J, Couch, FJ, Giles, GG, Kristensen, VN, Cox, A, Cunningham, JM, Pharoah, PDP, Dunning, AM, Edwards, SL, Easton, DF, Tomlinson, I, Spurdle, AB, Thompson, Deborah [0000-0003-1465-5799], Dennis, Joe [0000-0003-4591-1214], Wang, Jean [0000-0002-9139-0627], Tyrer, Jonathan [0000-0003-3724-4757], Pharoah, Paul [0000-0001-8494-732X], Dunning, Alison [0000-0001-6651-7166], Easton, Douglas [0000-0003-2444-3247], and Apollo - University of Cambridge Repository

Subjects
Humans, Female, Genetic Predisposition to Disease, Promoter Regions, Genetic, Polymorphism, Single Nucleotide, Chromosomes, Human, Pair 8, Endometrial Neoplasms, Genome-Wide Association Study
Abstract

We conducted a meta-analysis of three endometrial cancer genome-wide association studies (GWAS) and two follow-up phases totaling 7,737 endometrial cancer cases and 37,144 controls of European ancestry. Genome-wide imputation and meta-analysis identified five new risk loci of genome-wide significance at likely regulatory regions on chromosomes 13q22.1 (rs11841589, near KLF5), 6q22.31 (rs13328298, in LOC643623 and near HEY2 and NCOA7), 8q24.21 (rs4733613, telomeric to MYC), 15q15.1 (rs937213, in EIF2AK4, near BMF) and 14q32.33 (rs2498796, in AKT1, near SIVA1). We also found a second independent 8q24.21 signal (rs17232730). Functional studies of the 13q22.1 locus showed that rs9600103 (pairwise r(2) = 0.98 with rs11841589) is located in a region of active chromatin that interacts with the KLF5 promoter region. The rs9600103[T] allele that is protective in endometrial cancer suppressed gene expression in vitro, suggesting that regulation of the expression of KLF5, a gene linked to uterine development, is implicated in tumorigenesis. These findings provide enhanced insight into the genetic and biological basis of endometrial cancer.

Published
2016

28. No clinical utility of KRAS variant rs61764370 for ovarian or breast cancer

Author

Hollestelle, A, Van Der Baan, FH, Berchuck, A, Johnatty, SE, Aben, KK, Agnarsson, BA, Aittomäki, K, Alducci, E, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Antoniou, AC, Apicella, C, Arndt, V, Arnold, N, Arun, BK, Arver, B, Ashworth, A, Baglietto, L, Balleine, R, Bandera, EV, Barrowdale, D, Bean, YT, Beckmann, L, Beckmann, MW, Benitez, J, Berger, A, Berger, R, Beuselinck, B, Bisogna, M, Bjorge, L, Blomqvist, C, Bogdanova, NV, Bojesen, A, Bojesen, SE, Bolla, MK, Bonanni, B, Brand, JS, Brauch, H, Brenner, H, Brinton, L, Brooks-Wilson, A, Bruinsma, F, Brunet, J, Brüning, T, Budzilowska, A, Bunker, CH, Burwinkel, B, Butzow, R, Buys, SS, Caligo, MA, Campbell, I, Carter, J, Chang-Claude, J, Chanock, SJ, Claes, KBM, Collée, JM, Cook, LS, Couch, FJ, Cox, A, Cramer, D, Cross, SS, Cunningham, JM, Cybulski, C, Czene, K, Damiola, F, Dansonka-Mieszkowska, A, Darabi, H, De La Hoya, M, Defazio, A, Dennis, J, Devilee, P, and Dicks, EM

Abstract

© 2015 Elsevier Inc. All rights reserved. Objective Clinical genetic testing is commercially available for rs61764370, an inherited variant residing in a KRAS 3′ UTR microRNA binding site, based on suggested associations with increased ovarian and breast cancer risk as well as with survival time. However, prior studies, emphasizing particular subgroups, were relatively small. Therefore, we comprehensively evaluated ovarian and breast cancer risks as well as clinical outcome associated with rs61764370. Methods Centralized genotyping and analysis were performed for 140,012 women enrolled in the Ovarian Cancer Association Consortium (15,357 ovarian cancer patients; 30,816 controls), the Breast Cancer Association Consortium (33,530 breast cancer patients; 37,640 controls), and the Consortium of Modifiers of BRCA1 and BRCA2 (14,765 BRCA1 and 7904 BRCA2 mutation carriers). Results We found no association with risk of ovarian cancer (OR = 0.99, 95% CI 0.94-1.04, p = 0.74) or breast cancer (OR = 0.98, 95% CI 0.94-1.01, p = 0.19) and results were consistent among mutation carriers (BRCA1, ovarian cancer HR = 1.09, 95% CI 0.97-1.23, p = 0.14, breast cancer HR = 1.04, 95% CI 0.97-1.12, p = 0.27; BRCA2, ovarian cancer HR = 0.89, 95% CI 0.71-1.13, p = 0.34, breast cancer HR = 1.06, 95% CI 0.94-1.19, p = 0.35). Null results were also obtained for associations with overall survival following ovarian cancer (HR = 0.94, 95% CI 0.83-1.07, p = 0.38), breast cancer (HR = 0.96, 95% CI 0.87-1.06, p = 0.38), and all other previously-reported associations. Conclusions rs61764370 is not associated with risk of ovarian or breast cancer nor with clinical outcome for patients with these cancers. Therefore, genotyping this variant has no clinical utility related to the prediction or management of these cancers.

Published
2016

29. Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

Author

Couch, FJ, Kuchenbaecker, KB, Michailidou, K, Mendoza-Fandino, GA, Nord, S, Lilyquist, J, Olswold, C, Hallberg, E, Agata, S, Ahsan, H, Aittomäki, K, Ambrosone, C, Andrulis, IL, Anton-Culver, H, Arndt, V, Arun, BK, Arver, B, Barile, M, Barkardottir, RB, Barrowdale, D, Beckmann, L, Beckmann, MW, Benitez, J, Blank, SV, Blomqvist, C, Bogdanova, NV, Bojesen, SE, Bolla, MK, Bonanni, B, Brauch, H, Brenner, H, Burwinkel, B, Buys, SS, Caldes, T, Caligo, MA, Canzian, F, Carpenter, J, Chang-Claude, J, Chanock, SJ, Chung, WK, Claes, KBM, Cox, A, Cross, SS, Cunningham, JM, Czene, K, Daly, MB, Damiola, F, Darabi, H, De La Hoya, M, Devilee, P, Diez, O, Ding, YC, Dolcetti, R, Domchek, SM, Dorfling, CM, Dos-Santos-Silva, I, Dumont, M, Dunning, AM, Eccles, DM, Ehrencrona, H, Ekici, AB, Eliassen, H, Ellis, S, Fasching, PA, Figueroa, J, Flesch-Janys, D, Försti, A, Fostira, F, Foulkes, WD, Friebel, T, Friedman, E, Frost, D, Gabrielson, M, Gammon, MD, Ganz, PA, Gapstur, SM, Garber, J, Gaudet, MM, Gayther, SA, Gerdes, AM, Ghoussaini, M, Giles, GG, Glendon, G, Godwin, AK, Goldberg, MS, Goldgar, DE, González-Neira, A, Greene, MH, Gronwald, J, Guénel, P, Gunter, M, Haeberle, L, and Haiman, CA

Subjects
skin and connective tissue diseases
Abstract

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P

Published
2016

30. BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

Author

Meeks, H.D., Song, H.L., Michailidou, K., Bolla, M.K., Dennis, J., Wang, Q., Barrowdale, D., Frost, D., McGuffog, L., Ellis, S., Feng, B.J., Buys, S.S., Hopper, J.L., Southey, M.C., Tesoriero, A., James, P.A., Bruinsma, F., Campbell, I.G., Broeks, A., Schmidt, M.K., Hogervorst, F.B.L., Beckman, M.W., Fasching, P.A., Fletcher, O., Johnson, N., Sawyer, E.J., Riboli, E., Banerjee, S., Menon, U., Tomlinson, I., Burwinkel, B., Hamann, U., Marme, F., Rudolph, A., Janavicius, R., Tihomirova, L., Tung, N., Garber, J., Cramer, D., Terry, K.L., Poole, E.M., Tworoger, S.S., Dorfling, C.M., Rensburg, E.J. van, Godwin, A.K., Guenel, P., Truong, T., Stoppa-Lyonnet, D., Damiola, F., Mazoyer, S., Sinilnikova, O.M., Isaacs, C., Maugard, C., Bojesen, S.E., Flyger, H., Gerdes, A.M., Hansen, T.V.O., Jensen, A., Kjaer, S.K., Hogdall, C., Hogdall, E., Pedersen, I.S., Thomassen, M., Benitez, J., Gonzalez-Neira, A., Osorio, A., Hoya, M. de la, Segura, P.P., Diez, O., Lazaro, C., Brunet, J., Anton-Culver, H., Eunjung, L., John, E.M., Neuhausen, S.L., Ding, Y.C., Castillo, D., Weitzel, J.N., Ganz, P.A., Nussbaum, R.L., Chan, S.B., Karlan, B.Y., Lester, J., Wu, A., Gayther, S., Ramus, S.J., Sieh, W., Whittermore, A.S., Monteiro, A.N.A., Phelan, C.M., Terry, M.B., Piedmonte, M., Offit, K., Robson, M., Levine, D., Moysich, K.B., Cannioto, R., Olson, S.H., Daly, M.B., Nathanson, K.L., Domchek, S.M., Lu, K.H., Liang, D., Hildebrant, M.A.T., Ness, R., Modugno, F., Pearce, L., Goodman, M.T., Thompson, P.J., Brenner, H., Butterbach, K., Meindl, A., Hahnen, E., Wappenschmidt, B., Brauch, H., Bruning, T., Blomqvist, C., Khan, S., Nevanlinna, H., Pelttari, L.M., Aittomaki, K., Butzow, R., Bogdanova, N.V., Dork, T., Lindblom, A., Margolin, S., Rantala, J., Kosma, V.M., Mannermaa, A., Lambrechts, D., Neven, P., Claes, K.B.M., Maerken, T. van, Chang-Claude, J., Flesch-Janys, D., Heitz, F., Varon-Mateeva, R., Peterlongo, P., Radice, P., Viel, A., Barile, M., Peissel, B., Manoukian, S., Montagna, M., Oliani, C., Peixoto, A., Teixeira, M.R., Collavoli, A., Hallberg, E., Olson, J.E., Goode, E.L., Hart, S.N., Shimelis, H., Cunningham, J.M., Giles, G.G., Milne, R.L., Healey, S., Tucker, K., Haiman, C.A., Henderson, B.E., Goldberg, M.S., Tischkowitz, M., Simard, J., Soucy, P., Eccles, D.M., N. le, Borresen-Dale, A.L., Kristensen, V., Salvesen, H.B., Bjorge, L., Bandera, E.V., Risch, H., Zheng, W., Beeghly-Fadiel, A., Cai, H., Pylkas, K., Tollenaar, R.A.E.M., Ouweland, A.M.W. van der, Andrulis, I.L., Knight, J.A., Narod, S., Devilee, P., Winqvist, R., Figueroa, J., Greene, M.H., Mai, P.L., Loud, J.T., Garcia-Closas, M., Schoemaker, M.J., Czene, K., Darabi, H., McNeish, I., Siddiquil, N., Glasspool, R., Kwong, A., Park, S.K., Teo, S.H., Yoon, S.Y., Matsuo, K., Hosono, S., Woo, Y.L., Gao, Y.T., Foretova, L., Singer, C.F., Rappaport-Feurhauser, C., Friedman, E., Laitman, Y., Rennert, G., Imyanitov, E.N., Hulick, P.J., Olopade, O.I., Senter, L., Olah, E., Doherty, J.A., Schildkraut, J., Koppert, L.B., Kiemeney, L.A., Massuger, L.F.A.G., Cook, L.S., Pejovic, T., Li, J.M., Borg, A., Ofverholm, A., Rossing, M.A., Wentzensen, N., Henriksson, K., Cox, A., Cross, S.S., Pasini, B.J., Shah, M., Kabisch, M., Torres, D., Jakubowska, A., Lubinski, J., Gronwald, J., Agnarsson, B.A., Kupryjanczyk, J., Moes-Sosnowska, J., Fostira, F., Konstantopoulou, I., Slager, S., Jones, M., Antoniou, A.C., Berchuck, A., Swerdlow, A., Chenevix-Trench, G., Dunning, A.M., Pharoah, P.D.P., Hall, P., Easton, D.F., Couch, F.J., Spurdle, A.B., Goldgar, D.E., EMBRACE, kConFab Investigators, Australia Ovarian Canc Study Grp, HEBON, GEMO Study Collaborators, OCGN, PRostate Canc Assoc Grp, Damage and Repair in Cancer Development and Cancer Treatment (DARE), Targeted Gynaecologic Oncology (TARGON), Clinical Genetics, Obstetrics & Gynecology, Surgery, and [ 1 ] Univ Utah, Huntsman Canc Inst, Canc Control & Populat Sci, Salt Lake City, UT USA [ 2 ] Univ Cambridge, Dept Oncol, Ctr Canc Genet Epidemiol, Cambridge, England [ 3 ] Univ Cambridge, Dept Publ Hlth & Primary Care, Ctr Canc Genet Epidemiol, Cambridge, England [ 4 ] Univ Utah, Sch Med, Huntsman Canc Inst, Dept Dermatol, 2000 Circle Hope Dr, Salt Lake City, UT 84112 USA [ 5 ] Univ Utah, Sch Med, Dept Med, Huntsman Canc Inst, Salt Lake City, UT USA [ 6 ] Univ Melbourne, Melbourne Sch Populat & Global Hlth, Ctr Epidemiol & Biostat, Melbourne, Vic, Australia [ 7 ] Univ Melbourne, Dept Pathol, Melbourne, Vic, Australia [ 8 ] Univ Melbourne, Dept Pathol, Genet Epidemiol Lab, Parkville, Vic 3052, Australia [ 9 ] KConFab Kathleen Cuningham Consortium Res Familia, Peter MacCallum Canc Ctr, Melbourne, Vic, Australia [ 10 ] Peter MacCallum Canc Ctr, Familial Canc Ctr, Melbourne, Vic, Australia [ 11 ] Univ Melbourne, Dept Oncol, Melbourne, Vic, Australia [ 12 ] Canc Council Victoria, Canc Epidemiol Ctr, Melbourne, Vic, Australia [ 13 ] Univ Melbourne, Peter MacCallum Canc Ctr, Sir Peter MacCallum Dept Oncol, Parkville, Vic 3052, Australia [ 14 ] QIMR Berghofer Med Res Inst, Canc Div, Brisbane, Qld, Australia [ 15 ] Peter MacCallum Canc Inst, East Melbourne, Vic, Australia [ 16 ] Antoni van Leeuwenhoek Hosp, Netherlands Canc Inst, Amsterdam, Netherlands [ 17 ] Netherlands Canc Inst, Family Canc Clin, Amsterdam, Netherlands [ 18 ] Netherlands Canc Inst, Hereditary Breast & Ovarian Canc Res Grp Netherla, Coordinating Ctr, Amsterdam, Netherlands [ 19 ] Univ Erlangen Nurnberg, Comprehens Canc Ctr Erlangen EMN, Univ Hosp Erlangen, Dept Gynaecol & Ostetr, D-91054 Erlangen, Germany [ 20 ] Univ Calif Los Angeles, David Geffen Sch Med, Dept Med, Div Hematol & Oncol, Los Angeles, CA 90095 USA [ 21 ] Inst Canc Res, Div Breast Canc Res, London SW3 6JB, England [ 22 ] Inst Canc Res, Breakthrough Breast Canc Res Ctr, London SW3 6JB, England [ 23 ] Guys Hosp, Kings Coll London, Div Canc Studies, Res Oncol, London SE1 9RT, England [ 24 ] Univ London Imperial Coll Sci Technol & Med, Sch Publ Hlth, Dept Epidemiol & Biostat, London, England [ 25 ] Royal Marsden NHS Fdn Trust, London, England [ 26 ] Univ Coll London Elizabeth Garrett Anderson EGA, Inst Womens Hlth, Womens Canc, London, England [ 27 ] Univ Oxford, Wellcome Trust Ctr Human Genet, Oxford, England [ 28 ] Univ Oxford, Oxford Biomed Res Ctr, Oxford, England [ 29 ] German Canc Res Ctr, Div Mol Genet Epidemiol, Heidelberg, Germany [ 30 ] German Canc Res Ctr, Mol Genet Breast Canc, Heidelberg, Germany [ 31 ] Heidelberg Univ, Dept Obstet & Gynecol, Heidelberg, Germany [ 32 ] Heidelberg Univ, Natl Ctr Tumor Dis, Heidelberg, Germany [ 33 ] German Canc Res Ctr, Div Canc Epidemiol, Heidelberg, Germany [ 34 ] State Res Inst Ctr Innovat Med, Vilnius, Lithuania [ 35 ] Latvian Biomed Res & Study Ctr, Riga, Latvia [ 36 ] Beth Israel Deaconess Med Ctr, Dept Med Oncol, Boston, MA 02215 USA [ 37 ] Dana Farber Canc Inst, Canc Risk & Prevent Clin, Boston, MA 02115 USA [ 38 ] Brigham & Womens Hosp, Obstet & Gynecol Epidemiol Ctr, 75 Francis St, Boston, MA 02115 USA [ 39 ] Brigham & Womens Hosp, Channing Div Network Med, 75 Francis St, Boston, MA 02115 USA [ 40 ] Harvard Univ, Sch Med, Boston, MA 02115 USA [ 41 ] Harvard Univ, Sch Publ Hlth, Dept Epidemiol, 665 Huntington Ave, Boston, MA 02115 USA [ 42 ] Univ Pretoria, Dept Genet, ZA-0002 Pretoria, South Africa [ 43 ] Univ Kansas, Med Ctr, Dept Pathol & Lab Med, Kansas City, KS 66103 USA [ 44 ] Natl Inst Hlth & Med Res, Ctr Res Epidemiol & Populat Hlth CESP, Environm Epidemiol Canc, INSERM,U1018, Villejuif, France [ 45 ] Univ Paris Sud, Villejuif, France [ 46 ] UNICANCER Genet Grp, GEMO Study Natl Canc Genet Network, Paris, France [ 47 ] Inst Curie, Dept Tumour Biol, Paris, France [ 48 ] INSERM, U830, Inst Curie, Paris, France [ 49 ] Univ Paris 05, Sorbonne Paris Cite, Paris, France [ 50 ] Univ Lyon, Ctr Rech Cancerol Lyon, INSERM,U1052, CNRS UMR 5286, Lyon, France [ 51 ] Hosp Civils Pyon, Ctr Leon Berard, Unite Mixte Genet Constitutionelle Canc Frequents, Lyon, France [ 52 ] Georgetown Univ, Lombardi Comprehens Canc Ctr, Washington, DC USA [ 53 ] Hop Univ Strasbourg, CHRU Nouvel, Lab Diagnost Genet, Hop Civil, Strasbourg, France [ 54 ] Hop Univ Strasbourg, CHRU Nouvel, Serv Oncohematol, Hop Civil, Strasbourg, France [ 55 ] Univ Copenhagen, Fac Hlth & Med Sci, Copenhagen, Denmark [ 56 ] Copenhagen Univ Hosp, Dept Clin Biochem, Herlev Hosp, Herlev, Denmark [ 57 ] Copenhagen Univ Hosp, Herlev Hosp, Dept Breast Surg, Herlev, Denmark [ 58 ] Copenhagen Univ Hosp, Rigshosp, Dept Clin Genet, Copenhagen, Denmark [ 59 ] Copenhagen Univ Hosp, Rigshosp, Ctr Genom Med, Copenhagen, Denmark [ 60 ] Danish Canc Soc, Dept Virus Lifestyle & Genes, Res Ctr, Copenhagen, Denmark [ 61 ] Univ Copenhagen, Rigshosp, Dept Gynecol, DK-2100 Copenhagen, Denmark [ 62 ] Univ Copenhagen, Herlev Hosp, Dept Pathol, Mol Unit, Copenhagen, Denmark [ 63 ] Aalborg Univ Hosp, Dept Biochem, Sect Mol Diagnost, Aalborg, Denmark [ 64 ] Odense Univ Hosp, Dept Clin Genet, DK-5000 Odense C, Denmark [ 65 ] Spanish Natl Canc Ctr 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Greece [ 232 ] Duke Univ, Med Ctr, Dept Obstet & Gynecol, Durham, NC 27710 USA

Subjects
0301 basic medicine, Oncology, Male, Cancer Research, endocrine system diseases, LOCI, Estrogen receptor, FAMILY-HISTORY, Prostate cancer, 0302 clinical medicine, Ovarian Neoplasms/pathology, Prostate, Risk Factors, Brjóstakrabbamein, Odds Ratio, skin and connective tissue diseases, Ovarian Neoplasms, Women's cancers Radboud Institute for Molecular Life Sciences [Radboudumc 17], Prostatic Neoplasms/genetics, Research Support, Non-U.S. Gov't, SINGLE-NUCLEOTIDE POLYMORPHISMS, Middle Aged, BRCA2 Protein/genetics, PANCREATIC-CANCER, 3. Good health, SUSCEPTIBILITY GENE, medicine.anatomical_structure, Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], 030220 oncology & carcinogenesis, Codon, Terminator, Female, Risk Factors Substances, Adult, medicine.medical_specialty, Heterozygote, Breast Neoplasms, Blöðruhálskirtilskrabbamein, Breast Neoplasms/genetics, Biology, Polymorphism, Single Nucleotide, Risk Assessment, Article, Ovarian Neoplasms/genetics, 03 medical and health sciences, Breast cancer, SDG 3 - Good Health and Well-being, Research Support, N.I.H., Extramural, Internal medicine, Pancreatic cancer, Krabbameinsrannsóknir, medicine, Journal Article, Humans, Genetic Predisposition to Disease, Neoplasm Invasiveness, Lysine/genetics, Krabbamein, Aged, Gynecology, BRCA2 Protein, Proportional hazards model, Lysine, DNA RECOMBINATION, CONSORTIUM, GERM-LINE MUTATION, Prostatic Neoplasms, Odds ratio, Arfgengi, medicine.disease, ESTROGEN-RECEPTOR, 030104 developmental biology, Logistic Models, PTT12, Eggjastokkar, FANCONI-ANEMIA, Ovarian cancer
Abstract

Contains fulltext : 172007.pdf (Publisher’s version ) (Closed access) BACKGROUND: The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. METHODS: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. RESULTS: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10(-) (6)) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10(-3)). These associations were stronger for serous ovarian cancer and for estrogen receptor-negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10(-5) and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10(-5), respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. CONCLUSIONS: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations.

Published
2016

31. PALB2, CHEK2 and ATM rare variants and cancer risk:data from COGS

Author

Southey, M. C. (Melissa C.), Goldgar, D. E. (David E.), Winqvist, R. (Robert), Pylkäs, K. (Katri), Couch, F. (Fergus), Tischkowitz, M. (Marc), Foulkes, W. D. (William D.), Dennis, J. (Joe), Michailidou, K. (Kyriaki), van Rensburg, E. J. (Elizabeth J.), Heikkinen, T. (Tuomas), Nevanlinna, H. (Heli), Hopper, J. L. (John L.), Doerk, T. (Thilo), Claes, K. B. (Kathleen B. M.), Reis-Filho, J. (Jorge), Teo, Z. L. (Zhi Ling), Radice, P. (Paolo), Catucci, I. (Irene), Peterlongo, P. (Paolo), Tsimiklis, H. (Helen), Odefrey, F. A. (Fabrice A.), Dowty, J. G. (James G.), Schmidt, M. K. (Marjanka K.), Broeks, A. (Annegien), Hogervorst, F. B. (Frans B.), Verhoef, S. (Senno), Carpenter, J. (Jane), Clarke, C. (Christine), Scott, R. J. (Rodney J.), Fasching, P. A. (Peter A.), Haeberle, L. (Lothar), Ekici, A. B. (Arif B.), Beckmann, M. W. (Matthias W.), Peto, J. (Julian), dos-Santos-Silva, I. (Isabel), Fletcher, O. (Olivia), Johnson, N. (Nichola), Bolla, M. K. (Manjeet K.), Sawyer, E. J. (Elinor J.), Tomlinson, I. (Ian), Kerin, M. J. (Michael J.), Miller, N. (Nicola), Marme, F. (Federik), Burwinkel, B. (Barbara), Yang, R. (Rongxi), Guenel, P. (Pascal), Menegaux, F. (Florence), Sanchez, M. (Marie), Bojesen, S. (Stig), Nielsen, S. F. (Sune F.), Flyger, H. (Henrik), Benitez, J. (Javier), Pilar Zamora, M. (M.), Arias Perez, J. I. (Jose Ignacio), Menendez, P. (Primitiva), Anton-Culver, H. (Hoda), Neuhausen, S. (Susan), Ziogas, A. (Argyrios), Clarke, C. A. (Christina A.), Brenner, H. (Hermann), Arndt, V. (Volker), Stegmaier, C. (Christa), Brauch, H. (Hiltrud), Bruening, T. (Thomas), Ko, Y.-D. (Yon-Dschun), Muranen, T. A. (Taru A.), Aittomaki, K. (Kristiina), Blomqvist, C. (Carl), Bogdanova, N. V. (Natalia V.), Antonenkova, N. N. (Natalia N.), Lindblom, A. (Annika), Margolin, S. (Sara), Mannermaa, A. (Arto), Kataja, V. (Vesa), Kosma, V.-M. (Veli-Matti), Hartikainen, J. M. (Jaana M.), Spurdle, A. B. (Amanda B.), Wauters, E. (Els), Smeets, D. (Dominiek), Beuselinck, B. (Benoit), Floris, G. (Giuseppe), Chang-Claude, J. (Jenny), Rudolph, A. (Anja), Seibold, P. (Petra), Flesch-Janys, D. (Dieter), Olson, J. E. (Janet E.), Vachon, C. (Celine), Pankratz, V. S. (Vernon S.), McLean, C. (Catriona), Haiman, C. A. (Christopher A.), Henderson, B. E. (Brian E.), Schumacher, F. (Fredrick), Le Marchand, L. (Loic), Kristensen, V. (Vessela), Alnaes, G. G. (Grethe Grenaker), Zheng, W. (Wei), Hunter, D. J. (David J.), Lindstrom, S. (Sara), Hankinson, S. E. (Susan E.), Kraft, P. (Peter), Andrulis, I. (Irene), Knight, J. A. (Julia A.), Glendon, G. (Gord), Mulligan, A. M. (Anna Marie), Jukkola-Vuorinen, A. (Arja), Grip, M. (Mervi), Kauppila, S. (Saila), Devilee, P. (Peter), Tollenaar, R. A. (Robert A. E. M.), Seynaeve, C. (Caroline), Hollestelle, A. (Antoinette), Garcia-Closas, M. (Montserrat), Figueroa, J. (Jonine), Chanock, S. J. (Stephen J.), Lissowska, J. (Jolanta), Czene, K. (Kamila), Darabi, H. (Hatef), Eriksson, M. (Mikael), Eccles, D. M. (Diana M.), Rafiq, S. (Sajjad), Tapper, W. J. (William J.), Gerty, S. M. (Sue M.), Hooning, M. J. (Maartje J.), Martens, J. W. (John W. M.), Collee, J. M. (J. Margriet), Tilanus-Linthorst, M. (Madeleine), Hall, P. (Per), Li, J. (Jingmei), Brand, J. S. (Judith S.), Humphreys, K. (Keith), Cox, A. (Angela), Reed, M. W. (Malcolm W. R.), Luccarini, C. (Craig), Baynes, C. (Caroline), Dunning, A. M. (Alison M.), Hamann, U. (Ute), Torres, D. (Diana), Ulmer, H. U. (Hans Ulrich), Ruediger, T. (Thomas), Jakubowska, A. (Anna), Lubinski, J. (Jan), Jaworska, K. (Katarzyna), Durda, K. (Katarzyna), Slager, S. (Susan), Toland, A. E. (Amanda E.), Ambrosone, C. B. (Christine B.), Yannoukakos, D. (Drakoulis), Swerdlow, A. (Anthony), Ashworth, A. (Alan), Orr, N. (Nick), Jones, M. (Michael), Gonzalez-Neira, A. (Anna), Pita, G. (Guillermo), Rosario Alonso, M. (M.), Alvarez, N. (Nuria), Herrero, D. (Daniel), Tessier, D. C. (Daniel C.), Vincent, D. (Daniel), Bacot, F. (Francois), Simard, J. (Jacques), Dumont, M. (Martine), Soucy, P. (Penny), Eeles, R. (Rosalind), Muir, K. (Kenneth), Wiklund, F. (Fredrik), Gronberg, H. (Henrik), Schleutker, J. (Johanna), Nordestgaard, B. G. (Borge G.), Weischer, M. (Maren), Travis, R. C. (Ruth C.), Neal, D. (David), Donovan, J. L. (Jenny L.), Hamdy, F. C. (Freddie C.), Khaw, K.-T. (Kay-Tee), Stanford, J. L. (Janet L.), Blot, W. J. (William J.), Thibodeau, S. (Stephen), Schaid, D. J. (Daniel J.), Kelley, J. L. (Joseph L.), Maier, C. (Christiane), Kibel, A. S. (Adam S.), Cybulski, C. (Cezary), Cannon-Albright, L. (Lisa), Butterbach, K. (Katja), Park, J. (Jong), Kaneva, R. (Radka), Batra, J. (Jyotsna), Teixeira, M. R. (Manuel R.), Kote-Jarai, Z. (Zsofia), Al Olama, A. A. (Ali Amin), Benlloch, S. (Sara), Renner, S. P. (Stefan P.), Hartmann, A. (Arndt), Hein, A. (Alexander), Ruebner, M. (Matthias), Lambrechts, D. (Diether), Van Nieuwenhuysen, E. (Els), Vergote, I. (Ignace), Lambretchs, S. (Sandrina), Doherty, J. A. (Jennifer A.), Rossing, M. A. (Mary Anne), Nickels, S. (Stefan), Eilber, U. (Ursula), Wang-Gohrke, S. (Shan), Odunsi, K. (Kunle), Sucheston-Campbell, L. E. (Lara E.), Friel, G. (Grace), Lurie, G. (Galina), Killeen, J. L. (Jeffrey L.), Wilkens, L. R. (Lynne R.), Goodman, M. T. (Marc T.), Runnebaum, I. (Ingo), Hillemanns, P. A. (Peter A.), Pelttari, L. M. (Liisa M.), Butzow, R. (Ralf), Modugno, F. (Francesmary), Edwards, R. P. (Robert P.), Ness, R. B. (Roberta B.), Moysich, K. B. (Kirsten B.), du Bois, A. (Andreas), Heitz, F. (Florian), Harter, P. (Philipp), Kommoss, S. (Stefan), Karlan, B. Y. (Beth Y.), Walsh, C. (Christine), Lester, J. (Jenny), Jensen, A. (Allan), Kjaer, S. K. (Susanne Kruger), Hogdall, E. (Estrid), Peissel, B. (Bernard), Bonanni, B. (Bernardo), Bernard, L. (Loris), Goode, E. L. (Ellen L.), Fridley, B. L. (Brooke L.), Vierkant, R. A. (Robert A.), Cunningham, J. M. (Julie M.), Larson, M. C. (Melissa C.), Fogarty, Z. C. (Zachary C.), Kalli, K. R. (Kimberly R.), Liang, D. (Dong), Lu, K. H. (Karen H.), Hildebrandt, M. A. (Michelle A. T.), Wu, X. (Xifeng), Levine, D. A. (Douglas A.), Dao, F. (Fanny), Bisogna, M. (Maria), Berchuck, A. (Andrew), Iversen, E. S. (Edwin S.), Marks, J. R. (Jeffrey R.), Akushevich, L. (Lucy), Cramer, D. W. (Daniel W.), Schildkraut, J. (Joellen), Terry, K. L. (Kathryn L.), Poole, E. M. (Elizabeth M.), Stampfer, M. (Meir), Tworoger, S. S. (Shelley S.), Bandera, E. V. (Elisa V.), Orlow, I. (Irene), Olson, S. H. (Sara H.), Bjorge, L. (Line), Salvesen, H. B. (Helga B.), van Altena, A. M. (Anne M.), Aben, K. K. (Katja K. H.), Kiemeney, L. A. (Lambertus A.), Massuger, L. F. (Leon F. A. G.), Pejovic, T. (Tanja), Bean, Y. (Yukie), Brooks-Wilson, A. (Angela), Kelemen, L. E. (Linda E.), Cook, L. S. (Linda S.), Le, N. D. (Nhu D.), Grski, B. (Bohdan), Gronwald, J. (Jacek), Menkiszak, J. (Janusz), Hogdall, C. K. (Claus K.), Lundvall, L. (Lene), Nedergaard, L. (Lotte), Engelholm, S. A. (Svend Aage), Dicks, E. (Ed), Tyrer, J. (Jonathan), Campbell, I. (Ian), McNeish, I. (Iain), Paul, J. (James), Siddiqui, N. (Nadeem), Glasspool, R. (Rosalind), Whittemore, A. S. (Alice S.), Rothstein, J. H. (Joseph H.), McGuire, V. (Valerie), Sieh, W. (Weiva), Cai, H. (Hui), Shu, X.-O. (Xiao-Ou), Teten, R. T. (Rachel T.), Sutphen, R. (Rebecca), McLaughlin, J. R. (John R.), Narod, S. A. (Steven A.), Phelan, C. M. (Catherine M.), Monteiro, A. N. (Alvaro N.), Fenstermacher, D. (David), Lin, H.-Y. (Hui-Yi), Permuth, J. B. (Jennifer B.), Sellers, T. A. (Thomas A.), Chen, Y. A. (Y. Ann), Tsai, Y.-Y. (Ya-Yu), Chen, Z. (Zhihua), Gentry-Maharaj, A. (Aleksandra), Gayther, S. A. (Simon A.), Ramus, S. J. (Susan J.), Menon, U. (Usha), Wu, A. H. (Anna H.), Pearce, C. L. (Celeste L.), Van den Berg, D. (David), Pike, M. C. (Malcolm C.), Dansonka-Mieszkowska, A. (Agnieszka), Plisiecka-Halasa, J. (Joanna), Moes-Sosnowska, J. (Joanna), Kupryjanczyk, J. (Jolanta), Pharoah, P. D. (Paul D. P.), Song, H. (Honglin), Winship, I. (Ingrid), Chenevix-Trench, G. (Georgia), Giles, G. G. (Graham G.), Tavtigian, S. V. (Sean V.), Easton, D. F. (Doug F.), and Milne, R. L. (Roger L.)

Subjects
skin and connective tissue diseases
Abstract

Background: The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study. Methods: We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T>G and c.3113G>A, CHEK2 c.349A>G, c.538C>T, c.715G>A, c.1036C>T, c.1312G>T, and c.1343T>G and ATM c.7271T>G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant. Results: For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p = 7.1 × 10⁻⁵), PALB2 c.3113G>A OR 4.21 (95% CI 1.84 to 9.60, p = 6.9 × 10⁻⁸) and ATM c.7271T>G OR 11.0 (95% CI 1.42 to 85.7, p = 0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A>G OR 2.26 (95% CI 1.29 to 3.95), c.1036C>T OR 5.06 (95% CI 1.09 to 23.5) and c.538C>T OR 1.33 (95% CI 1.05 to 1.67) (p ≤ 0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T>G OR 3.03 (95% CI 1.53 to 6.03, p = 0.0006) for African men and CHEK2 c.1312G>T OR 2.21 (95% CI 1.06 to 4.63, p = 0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants. Conclusions: This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.

Published
2016

32. Association of breast cancer risk with genetic variants showing differential allelic expression: Identification of a novel breast cancer susceptibility locus at 4q21

Author

Hamdi, Y, Soucy, P, Adoue, V, Michailidou, K, Canisius, S, Lemaçon, A, Droit, A, Andrulis, IL, Anton-Culver, H, Arndt, V, Baynes, C, Blomqvist, C, Bogdanova, NV, Bojesen, SE, Bolla, MK, Bonanni, B, Borresen-Dale, AL, Brand, JS, Brauch, H, Brenner, H, Broeks, A, Burwinkel, B, Chang-Claude, J, Couch, FJ, Cox, A, Cross, SS, Czene, K, Darabi, H, Dennis, J, Devilee, P, Dörk, T, Dos-Santos-Silva, I, Eriksson, M, Fasching, PA, Figueroa, J, Flyger, H, García-Closas, M, Giles, GG, Goldberg, MS, González-Neira, A, Grenaker-Alnæs, G, Guénel, P, Haeberle, L, Haiman, CA, Hamann, U, Hallberg, E, Hooning, MJ, Hopper, JL, Jakubowska, A, Jones, M, Kabisch, M, Kataja, V, Lambrechts, D, Le Marchand, L, Lindblom, A, Lubinski, J, Mannermaa, A, Maranian, M, Margolin, S, Marme, F, Milne, RL, Neuhausen, SL, Nevanlinna, H, Neven, P, Olswold, C, Peto, J, Plaseska-Karanfilska, D, Pylkäs, K, Radice, P, Rudolph, A, Sawyer, EJ, Schmidt, MK, Shu, XO, Southey, MC, and Swerdlow, A

Abstract

There are significant inter-individual differences in the levels of gene expression. Through modulation of gene expression, cis-acting variants represent an important source of phenotypic variation. Consequently, cis-regulatory SNPs associated with differential allelic expression are functional candidates for further investigation as disease-causing variants. To investigate whether common variants associated with differential allelic expression were involved in breast cancer susceptibility, a list of genes was established on the basis of their involvement in cancer related pathways and/or mechanisms. Thereafter, using data from a genome-wide map of allelic expression associated SNPs, 313 genetic variants were selected and their association with breast cancer risk was then evaluated in 46,451 breast cancer cases and 42,599 controls of European ancestry ascertained from 41 studies participating in the Breast Cancer Association Consortium. The associations were evaluated with overall breast cancer risk and with estrogen receptor negative and positive disease. One novel breast cancer susceptibility locus on 4q21 (rs11099601) was identified (OR = 1.05, P = 5.6x10-6). rs11099601 lies in a 135 kb linkage disequilibrium block containing several genes, including, HELQ, encoding the protein HEL308 a DNA dependant ATPase and DNA Helicase involved in DNA repair, MRPS18C encoding the Mitochondrial Ribosomal Protein S18C and FAM175A (ABRAXAS), encoding a BRCA1 BRCT domain-interacting protein involved in DNA damage response and double-strand break (DSB) repair. Expression QTL analysis in breast cancer tissue showed rs11099601 to be associated with HELQ (P = 8.28x10-14), MRPS18C (P = 1.94x10-27) and FAM175A (P = 3.83x10-3), explaining about 20%, 14% and 1%, respectively of the variance in expression of these genes in breast carcinomas.

Published
2016

33. SNP-SNP interaction analysis of NF-kappa B signaling pathway on breast cancer survival

Author

Jamshidi, M., Fagerholm, R., Khan, S., Aittomaki, K., Czene, K., Darabi, H., Li, J.M., Andrulis, I.L., Chang-Claude, J., Devilee, P., Fasching, P.A., Michailidou, K., Bolla, M.K., Dennis, J., Wang, Q., Guo, Q., Rhenius, V., Cornelissen, S., Rudolph, A., Knight, J.A., Loehberg, C.R., Burwinkel, B., Marme, F., Hopper, J.L., Southey, M.C., Bojesen, S.E., Flyger, H., Brenner, H., Holleczek, B., Margolin, S., Mannermaa, A., Kosma, V.M., Dyck, L. van, Nevelsteen, I., Couch, F.J., Olson, J.E., Giles, G.G., McLean, C., Haiman, C.A., Henderson, B.E., Winqvist, R., Pylkas, K., Tollenaar, R.A.E.M., Garcia-Closas, M., Figueroa, J., Hooning, M.J., Martens, J.W.M., Cox, A., Cross, S.S., Simard, J., Dunning, A.M., Easton, D.F., Pharoah, P.D.P., Hall, P., Blomqvist, C., Schmidt, M.K., Nevanlinna, H., kConFab Investigators, Department of Obstetrics and Gynecology, Clinicum, Medicum, Kristiina Aittomäki / Principal Investigator, Department of Medical and Clinical Genetics, and Department of Oncology

Subjects
Oncology, medicine.medical_specialty, GENES, In silico, 3122 Cancers, Single-nucleotide polymorphism, Breast Neoplasms, Biology, Bioinformatics, ANNOTATION, Polymorphism, Single Nucleotide, survival analysis, ACTIVATION, Breast cancer, breast cancer, 3123 Gynaecology and paediatrics, Internal medicine, Genetic variation, medicine, Biomarkers, Tumor, SNP, Humans, Neoplasm Invasiveness, TRANSCRIPTION, Allele, Survival rate, Survival analysis, POLYMORPHISMS, Neoplasm Staging, NF-κB pathway, IDENTIFICATION, NF-kappa B, NF-kappa B pathway, CHEMOTHERAPY, medicine.disease, Prognosis, 3. Good health, FALSE DISCOVERY RATE, Survival Rate, SNP-SNP interaction, CELLS, Female, Neoplasm Grading, Research Paper, Signal Transduction
Abstract

In breast cancer, constitutive activation of NF-κB has been reported, however, the impact of genetic variation of the pathway on patient prognosis has been little studied. Furthermore, a combination of genetic variants, rather than single polymorphisms, may affect disease prognosis. Here, in an extensive dataset (n = 30,431) from the Breast Cancer Association Consortium, we investigated the association of 917 SNPs in 75 genes in the NF-κB pathway with breast cancer prognosis. We explored SNP-SNP interactions on survival using the likelihood-ratio test comparing multivariate Cox’ egression models of SNP pairs without and with an interaction term. We found two interacting pairs associating with prognosis: patients simultaneously homozygous for the rare alleles of rs5996080 and rs7973914 had worse survival (HRinteraction 6.98, 95% CI=3.3-14.4, P=1.42E-07), and patients carrying at least one rare allele for rs17243893 and rs57890595 had better survival (HRinteraction 0.51, 95% CI=0.3-0.6, P = 2.19E-05). Based on in silico functional analyses and literature, we speculate that the rs5996080 and rs7973914 loci may affect the BAFFR and TNFR1/TNFR3 receptors and breast cancer survival, possibly by disturbing both the canonical and non-canonical NF-κB pathways or their dynamics, whereas, rs17243893-rs57890595 interaction on survival may be mediated through TRAF2-TRAIL-R4 interplay. These results warrant further validation and functional analyses. ispartof: Oncotarget vol:6 issue:35 pages:37979-94 ispartof: location:United States status: published

Published
2015

34. SNP-SNP interaction analysis of NF-κB signaling pathway on breast cancer survival

Author

Jamshidi, M., Fagerholm, R., Khan, S., Aittomäki, K., Czene, K., Darabi, H., Li, J., Andrulis, I.L., Chang-Claude, J., Devilee, P., Fasching, P.A., Michailidou, K., Bolla, M.K., Dennis, J., Wang, Q., Guo, Q., Rhenius, V., Cornelissen, S., Rudolph, A., Knight, J.A., Loehberg, C.R., Burwinkel, B., Marme, F., Hopper, J.L., Southey, M.C., Bojesen, S.E., Flyger, H., Brenner, H., Holleczek, B., Margolin, S., Mannermaa, A., Kosma, V.M., Investigators, K., Van Dyck, L., Nevelsteen, I., Couch, F.J., Olson, J.E., Giles, G.G., McLean, C., Haiman, C.A., Henderson, B.E., Winqvist, R., Pylkäs, K., Tollenaar, R.A., García-Closas, M., Figueroa, J., Hooning, M.J., Martens, J.W., Cox, A., Cross, S.S., Simard, J., Dunning, A.M., Easton, D.F., Pharoah, P.D., Hall, P., Blomqvist, C., Schmidt, M.K., and Nevanlinna, H.

Abstract

In breast cancer, constitutive activation of NF-κB has been reported, however, the impact of genetic variation of the pathway on patient prognosis has been little studied. Furthermore, a combination of genetic variants, rather than single polymorphisms, may affect disease prognosis. Here, in an extensive dataset (n = 30,431) from the Breast Cancer Association Consortium, we investigated the association of 917 SNPs in 75 genes in the NF-κB pathway with breast cancer prognosis. We explored SNP-SNP interactions on survival using the likelihood-ratio test comparing multivariate Cox' regression models of SNP pairs without and with an interaction term. We found two interacting pairs associating with prognosis: patients simultaneously homozygous for the rare alleles of rs5996080 and rs7973914 had worse survival (HRinteraction 6.98, 95% CI=3.3-14.4, P=1.42E-07), and patients carrying at least one rare allele for rs17243893 and rs57890595 had better survival (HRinteraction 0.51, 95% CI=0.3-0.6, P = 2.19E-05). Based on in silico functional analyses and literature, we speculate that the rs5996080 and rs7973914 loci may affect the BAFFR and TNFR1/TNFR3 receptors and breast cancer survival, possibly by disturbing both the canonical and non-canonical NF-κB pathways or their dynamics, whereas, rs17243893-rs57890595 interaction on survival may be mediated through TRAF2-TRAIL-R4 interplay. These results warrant further validation and functional analyses.

Published
2015

35. Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants

Author

Mavaddat, N., Pharoah, P.D.P., Michailidou, K., Tyrer, J., Brook, M.N., Bolla, M.K., Wang, Q., Dennis, J., Dunning, A.M., Shah, M., Luben, R., Brown, J., Bojesen, S.E., Nordestgaard, B.G., Nielsen, S.F., Flyger, H., Czene, K., Darabi, H., Eriksson, M., Peto, J., dos-Santos-Silva, I., Dudbridge, F., Johnson, N., Schmidt, M.K., Broeks, A., Verhoef, S., Rutgers, E.J., Swerdlow, A., Ashworth, A., Orr, N., Schoemaker, M.J., Figueroa, J., Chanock, S.J., Brinton, L., Lissowska, J., Couch, F.J., Olson, J.E., Vachon, C., Pankratz, V.S., Lambrechts, D., Wildiers, H., Ongeval, C. van, Limbergen, E. van, Kristensen, V., Alnaes, G.G., Nord, S., Borresen-Dale, A.L., Nevanlinna, H., Muranen, T.A., Aittomaki, K., Blomqvist, C., Chang-Claude, J., Rudolph, A., Seibold, P., Flesch-Janys, D., Fasching, P.A., Haeberle, L., Ekici, A.B., Beckmann, M.W., Burwinkel, B., Marme, F., Schneeweiss, A., Sohn, C., Trentham-Dietz, A., Newcomb, P., Titus, L., Egan, K.M., Hunter, D.J., Lindstrom, S., Tamimi, R.M., Kraft, P., Rahman, N., Turnbull, C., Renwick, A., Seal, S., Li, J.M., Liu, J.J., Humphreys, K., Benitez, J., Zamora, M.P., Perez, J.I.A., Menendez, P., Jakubowska, A., Lubinski, J., Jaworska-Bieniek, K., Durda, K., Bogdanova, N.V., Antonenkova, N.N., Dork, T., Anton-Culver, H., Neuhausen, S.L., Ziogas, A., Bernstein, L., Devilee, P., Tollenaar, R.A.E.M., Seynaeve, C., Asperen, C.J. van, Cox, A., Cross, S.S., Reed, M.W.R., Khusnutdinova, E., Bermisheva, M., Prokofyeva, D., Takhirova, Z., Meindl, A., Schmutzler, R.K., Sutter, C., Yang, R.X., Schurmann, P., Bremer, M., Christiansen, H., Park-Simon, T.W., Hillemanns, P., Guenel, P., Truong, T., Menegaux, F., Sanchez, M., Radice, P., Peterlongo, P., Manoukian, S., Pensotti, V., Hopper, J.L., Tsimiklis, H., Apicella, C., Southey, M.C., Brauch, H., Bruning, T., Ko, Y.D., Sigurdson, A.J., Doody, M.M., Hamann, U., Torres, D., Ulmer, H.U., Forsti, A., Sawyer, E.J., Tomlinson, I., Kerin, M.J., Miller, N., Andrulis, I.L., Knight, J.A., Glendon, G., Mulligan, A.M., Chenevix-Trench, G., Balleine, R., Giles, G.G., Milne, R.L., McLean, C., Lindblom, A., Margolin, S., Haiman, C.A., Henderson, B.E., Schumacher, F., Marchand, L. le, Eilber, U., Wang-Gohrke, S., Hooning, M.J., Hollestelle, A., Ouweland, A.M.W. van den, Koppert, L.B., Carpenter, J., Clarke, C., Scott, R., Mannermaa, A., Kataja, V., Kosma, V.M., Hartikainen, J.M., Brenner, H., Arndt, V., Stegmaier, C., Dieffenbach, A.K., Winqvist, R., Pylkas, K., Jukkola-Vuorinen, A., Grip, M., Offit, K., Vijai, J., Robson, M., Rau-Murthy, R., Dwek, M., Swann, R., Perkins, K.A., Goldberg, M.S., Labreche, F., Dumont, M., Eccles, D.M., Tapper, W.J., Rafiq, S., John, E.M., Whittemore, A.S., Slager, S., Yannoukakos, D., Toland, A.E., Yao, S., Zheng, W., Halverson, S.L., Gonzalez-Neira, A., Pita, G., Alonso, M.R., Alvarez, N., Herrero, D., Tessier, D.C., Vincent, D., Bacot, F., Luccarini, C., Baynes, C., Ahmed, S., Maranian, M., Healey, C.S., Simard, J., Hall, P., Easton, D.F., Garcia-Closas, M., Clinical Genetics, Medical Oncology, Surgery, Department of Obstetrics and Gynecology, Clinicum, Medicum, Kristiina Aittomäki / Principal Investigator, Department of Medical and Clinical Genetics, Department of Oncology, HUS Gynecology and Obstetrics, Mavaddat, Nasim [0000-0003-0307-055X], Pharoah, Paul [0000-0001-8494-732X], Tyrer, Jonathan [0000-0003-3724-4757], Wang, Jean [0000-0002-9139-0627], Dennis, Joe [0000-0003-4591-1214], Dunning, Alison [0000-0001-6651-7166], Luben, Robert [0000-0002-5088-6343], Easton, Douglas [0000-0003-2444-3247], and Apollo - University of Cambridge Repository

Subjects
Adult, Genotype, 3122 Cancers, Breast Neoplasms, consortium, Polymorphism, Single Nucleotide, Risk Assessment, Article, prevention, SDG 3 - Good Health and Well-being, Predictive Value of Tests, Risk Factors, 3123 Gynaecology and paediatrics, Biomarkers, Tumor, Odds Ratio, Humans, Genetic Predisposition to Disease, family-history, Aged, prostate, Gene Expression Profiling, subtypes, Middle Aged, susceptibility loci, Europe, Gene Expression Regulation, Neoplastic, Receptors, Estrogen, Tumor Markers, Biological, Cancer and Oncology, genome-wide association, Female, women
Abstract

Background: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. Methods: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. Results: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1 of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. Conclusions: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report. © 2015 © The Author 2015. Published by Oxford University Press.

Published
2015

36. Identification of novel genetic markers of breast cancer survival

Author

Guo, Q., Schmidt, M.K., Kraft, P., Canisius, S., Chen, C., Khan, S., Tyrer, J., Bolla, M.K., Wang, Q., Dennis, J., Michailidou, K., Lush, M., Kar, S., Beesley, J., Dunning, A.M., Shah, M., Czene, K., Darabi, H., Eriksson, M., Lambrechts, D., Weltens, C., Leunen, K., Bojesen, S.E., Nordestgaard, B.G., Nielsen, S.F., Flyger, H., Chang-Claude, J., Rudolph, A., Seibold, P., Flesch-Janys, D., Blomqvist, C., Aittomaki, K., Fagerholm, R., Muranen, T.A., Couch, F.J., Olson, J.E., Vachon, C., Andrulis, I.L., Knight, J.A., Glendon, G., Mulligan, A.M., Broeks, A., Hogervorst, F.B., Haiman, C.A., Henderson, B.E., Schumacher, F., Marchand, L. le, Hopper, J.L., Tsimiklis, H., Apicella, C., Southey, M.C., Cox, A., Cross, S.S., Reed, M.W.R., Giles, G.G., Milne, R.L., McLean, C., Winqvist, R., Pylkas, K., Jukkola-Vuorinen, A., Grip, M., Hooning, M.J., Hollestelle, A., Martens, J.W.M., Ouweland, A.M.W. van den, Marme, F., Schneeweiss, A., Yang, R.X., Burwinkel, B., Figueroa, J., Chanock, S.J., Lissowska, J., Sawyer, E.J., Tomlinson, I., Kerin, M.J., Miller, N., Brenner, H., Dieffenbach, A.K., Arndt, V., Holleczek, B., Mannermaa, A., Kataja, V., Kosma, V.M., Hartikainen, J.M., Li, J.M., Brand, J.S., Humphreys, K., Devilee, P., Tollenaar, R.A.E.M., Seynaeve, C., Radice, P., Peterlongo, P., Bonanni, B., Mariani, P., Fasching, P.A., Beckmann, M.W., Hein, A., Ekici, A.B., Chenevix-Trench, G., Balleine, R., Phillips, K.A., Benitez, J., Zamora, M.P., Perez, J.I.A., Menendez, P., Jakubowska, A., Lubinski, J., Jaworska-Bieniek, K., Durda, K., Hamann, U., Kabisch, M., Ulmer, H.U., Rudiger, T., Margolin, S., Kristensen, V., Nord, S., Evans, D.G., Abraham, J.E., Earl, H.M., Hiller, L., Dunn, J.A., Bowden, S., Berg, C., Campa, D., Diver, W.R., Gapstur, S.M., Gaudet, M.M., Hankinson, S.E., Hoover, R.N., Husing, A., Kaaks, R., Machiela, M.J., Willett, W., Barrdahl, M., Canzian, F., Chin, S.F., Caldas, C., Hunter, D.J., Lindstrom, S., Garcia-Closas, M., Hall, P., Easton, D.F., Eccles, D.M., Rahman, N., Nevanlinna, H., Pharoah, P.D.P., kConFab Investigators, Tyrer, Jonathan [0000-0003-3724-4757], Wang, Jean [0000-0002-9139-0627], Dennis, Joe [0000-0003-4591-1214], Dunning, Alison [0000-0001-6651-7166], Abraham, Jean [0000-0003-0688-4807], Earl, Helena [0000-0003-1549-8094], Chin, Suet-Feung [0000-0001-5697-1082], Caldas, Carlos [0000-0003-3547-1489], Easton, Douglas [0000-0003-2444-3247], Pharoah, Paul [0000-0001-8494-732X], and Apollo - University of Cambridge Repository

Subjects
Genetic Markers, Genotype, Receptors, Estrogen, Humans, Breast Neoplasms, Female, Genetic Predisposition to Disease, Prognosis, Polymorphism, Single Nucleotide, Survival Analysis, White People
Abstract

BACKGROUND: Survival after a diagnosis of breast cancer varies considerably between patients, and some of this variation may be because of germline genetic variation. We aimed to identify genetic markers associated with breast cancer-specific survival. METHODS: We conducted a large meta-analysis of studies in populations of European ancestry, including 37954 patients with 2900 deaths from breast cancer. Each study had been genotyped for between 200000 and 900000 single nucleotide polymorphisms (SNPs) across the genome; genotypes for nine million common variants were imputed using a common reference panel from the 1000 Genomes Project. We also carried out subtype-specific analyses based on 6881 estrogen receptor (ER)-negative patients (920 events) and 23059 ER-positive patients (1333 events). All statistical tests were two-sided. RESULTS: We identified one new locus (rs2059614 at 11q24.2) associated with survival in ER-negative breast cancer cases (hazard ratio [HR] = 1.95, 95% confidence interval [CI] = 1.55 to 2.47, P = 1.91 x 10(-8)). Genotyping a subset of 2113 case patients, of which 300 were ER negative, provided supporting evidence for the quality of the imputation. The association in this set of case patients was stronger for the observed genotypes than for the imputed genotypes. A second locus (rs148760487 at 2q24.2) was associated at genome-wide statistical significance in initial analyses; the association was similar in ER-positive and ER-negative case patients. Here the results of genotyping suggested that the finding was less robust. CONCLUSIONS: This is currently the largest study investigating genetic variation associated with breast cancer survival. Our results have potential clinical implications, as they confirm that germline genotype can provide prognostic information in addition to standard tumor prognostic factors.

Published
2015

37. Common germline polymorphisms\ud associated with breast cancer-specific survival

Author

Pirie, A., Guo, Q., Kraft, P., Canisius, S., Eccles, D.M., Rahman, N., Nevanlinna, H., Chen, C., Khan, S., Tyrer, J., Bolla, M.K., Wang, Q., Dennis, J., Michailidou, K., Lush, M., Dunning, A.M., Shah, M., Czene, K., Darabi, H., Eriksson, M., Lambrechts, D., Weltens, C., Leunen, K., van Ongeval, C., Nordestgaard, B.G., Nielsen, S.F., Flyger, H., Rudolph, A., Seibold, P., Flesch-Janys, D., Blomqvist, C., Aittomaki, K., Fagerholm, R., Muranen, T.A., Olsen, J.E., Hallberg, E., Vachon, C., Knight, J.A., Glendon, G., Mulligan, A.M., Broeks, A., Cornelissen, S., Haiman, C.A., Henderson, B.E., Schumacher, F., Le Marchand, L., Hopper, J.L., Tsimiklis, H., Apicella, C., Southey, M.C., Cross, S.S., Reed, M.W.R., Giles, G.G., Milne, R.L., McLean, C., Winqvist, R., Pylkas, K., Jukkola-Vuorinen, A., Grip, M., Hooning, M.J., Hollestelle, A., Martens, J.W.M., van den Ouweland, A.M.W., Marme, F., Schneeweiss, A., Yang, R., Burwinkel, B., Figueroa, J., Chanock, S.J., Lissowska, J., Sawyer, E.J., Tomlinson, I., Kerin, M.J., Miller, N., Brenner, H., Butterbach, K., Holleczek, B., Kataja, V., Kosma, V-M., Hartikainen, J.M., Li, J., Brand, J.S., Humphreys, K., Devilee, P., Tollenaar, R.A.E.M., Seynaeve, C., Radice, P., Peterlongo, P., Manoukian, S., Ficarazzi, F., Beckmann, M.W., Hein, A., Ekici, A.B., Balleine, R., Phillips, K-A., Benitez, J., Zamora, M.P., Perez, J.I.A., Menendez, P., Jakubowska, A., Lubinski, J., Gronwald, J., Durda, K., Hamann, U., Kabisch, M., Ulmer, H.U., Ruediger, T., Margolin, S., Kristensen, V., Nord, S., Evans, D.G., Abraham, J., Earl, H., Poole, C.J., Hiller, L., Dunn, J.A., Bowden, S., Campa, D., Diver, W.R., Gapstur, S.M., Gaudet, M.M., Hankinson, S., Hoover, R.N., Husing, A., Kaaks, R., Machiela, M.J., Willett, W., Barrdahl, M., Canzian, F., Chin, S-F., Caldas, C., Hunter, D.J., Lindstrom, S., Garcia-Closas, M., Couch, F.J., Investigators, kConFab, Chenevix-Trench, G., Mannermaa, A., Andrulis, I.L., Hall, P., Chang-Claude, J., Easton, D.F., Bojesen, S.E., Cox, A., Fasching, P.A., Pharoah, P.D.P., Schmidt, M.K., and Investigators, NBCS

Abstract

Introduction: Previous studies have identified common germline variants nominally associated with breast cancer\ud survival. These associations have not been widely replicated in further studies. The purpose of this study was to\ud evaluate the association of previously reported SNPs with breast cancer-specific survival using data from a pooled\ud analysis of eight breast cancer survival genome-wide association studies (GWAS) from the Breast Cancer Association\ud Consortium.\ud Methods: A literature review was conducted of all previously published associations between common germline\ud variants and three survival outcomes: breast cancer-specific survival, overall survival and disease-free survival.\ud All associations that reached the nominal significance level of P value

Published
2015

38. Large-Scale Genomic Analyses Link Reproductive Aging to Hypothalamic Signaling, Breast Cancer Susceptibility, and BRCA1-Mediated DNA Repair EDITORIAL COMMENT

Author

Day, FR, Ruth, KS, Thompson, DJ, Lunetta, KL, Pervjakova, N, Chasman, DI, Stolk, Lisette, Finucane, HK, Sulem, P, Bulik-Sullivan, B, Esko, T, Johnson, AD, Elks, CE, Franceschini, N, He, C, Altmaier, E, Brody, JA, Franke, LL, Huffman, JE, Keller, MF, McArdle, PF, Nutile, T, Porcu, E, Robino, A, Rose, LM, Schick, UM, Smith, JA, Teumer, A, Traglia, M, Vuckovic, D, Yao, J, Zhao, W, Albrecht, E, Amin, Najaf, Corre, T, Hottenga, JJ (Jouke Jan), Mangino, M, Smith, AV, Tanaka, T, Abecasis, GR, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Arndt, V, Arnold, AM, Barbieri, C, Beckmann, MW, Beeghly-Fadiel, A, Benitez, J, Bernstein, L, Bielinski, SJ, Blomqvist, C, Boerwinkle, E, Bogdanova, NV, Bojesen, SE, Bolla, MK, Borresen-Dale, AL, Boutin, TS, Brauch, H, Brenner, H, Bruning, T, Burwinkel, B, Campbell, A (Archie), Campbell, H, Chanock, SJ, Chapman, JR, Chen, YDI, Chenevix-Trench, G, Couch, FJ, Coviello, AD, Cox, A, Czene, K, Darabi, H, de Vivo, I, Demerath, EW, Dennis, J, Devilee, P, Dork, T, dos-Santos-Silva, I, Dunning, AM, Eicher, JD, Fasching, PA, Faul, JD, Figueroa, J, Flesch-Janys, D, Gandin, I, Garcia, ME, Garcia-Closas, M, Giles, GG, Girotto, GG, Goldberg, MS, Gonzalez-Neira, A, Goodarzi, MO, Grove, ML, Gudbjartsson, DF, Guenel, P, Guo, XQ, Haiman, CA, Hall, P, Hamann, U, Henderson, BE, Hocking, LJ, Hofman, Bert, Homuth, G, Hooning, Maartje, Hopper, JL, Hu, FB, Huang, JY, Humphreys, K, Hunter, DJ, Jakubowska, A, Jones, SE, Kabisch, M, Karasik, D, Knight, JA, Kolcic, I, Kooperberg, C, Kosma, VM, Kriebel, J, Kristensen, V, Lambrechts, D, Langenberg, C, Li, JM, Li, X, Lindstrom, S, Liu, YM, Luan, JA, Lubinski, J, Magi, R, Mannermaa, A, Manz, J, Margolin, S, Marten, J, Martin, NG, Masciullo, C, Meindl, A, Michailidou, K, Mihailov, E, Milani, L, Milne, RL, Muller-Nurasyid, M, Nalls, M, Neale, BM, Nevanlinna, H, Neven, P, Newman, AB, Nordestgaard, BG, Olson, JE, Padmanabhan, S, Peterlongo, P, Peters, U, Petersmann, A, Peto, J, Pharoah, PDP, Pirastu, NN, Pirie, A, Pistis, G, Polasek, O, Porteous, D, Psaty, BM, Pylkas, K, Radice, P, Raffel, LJ, Rivadeneira, Fernando, Rudan, I, Rudolph, A, Ruggiero, D, Sala, CF, Sanna, S, Sawyer, EJ, Schlessinger, D, Schmidt, MK (Marjanka), Schmidt, F, Schmutzler, RK, Schoemaker, MJ, Scott, RA, Seynaeve, Caroline, Simard, J, Sorice, R, Southey, MC, Stockl, D, Strauch, K, Swerdlow, A, Taylor, KD, Thorsteinsdottir, U, Toland, AE, Tomlinson, I, Truong, T, Tryggvadottir, L, Turner, ST, Vozzi, D, Wang, Q (Qing), Wellons, M, Willemsen, G, Wilson, JF, Winqvist, R, Wolffenbuttel, BBHR, Wright, AF, Yannoukakos, D, Zemunik, T, Zheng, W, Zygmunt, M, Bergmann, S, Boomsma, DI, Buring, JE, Ferrucci, L, Montgomery, GW, Gudnason, V, Spector, TD, Duijn, Cornelia, Alizadeh, BZ, Ciullo, M, Crisponi, L, Easton, DF, Gasparini, PP, Gieger, C, Harris, TB, Hayward, C, Kardia, SLR, Kraft, P, McKnight, B, Metspalu, A, Morrison, AC, Reiner, AP, Ridker, PM, Rotter, JI, Toniolo, D, Uitterlinden, André, Ulivi, S, Volzke, H, Wareham, NJ, Weir, DR, Yerges-Armstrong, LM, Price, AL, Stefansson, K, Visser, Jenny, Ong, KK, Chang-Claude, J, Murabito, JM, Perry, JRB, Murray, A, Systems Ecology, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, Internal Medicine, Epidemiology, Medical Oncology, and Clinical Genetics

Subjects
SDG 3 - Good Health and Well-being
Published
2015

39. Meta-analysis of genome-wide association studies identifies common susceptibility polymorphisms for colorectal and endometrial cancer near SH2B3 and TSHZ1

Author

Cheng, T.H.T., Thompson, D., Painter, J., O'Mara, T., Gorman, M., Martin, L., Palles, C., Jones, A., Buchanan, D.D., Win, A.K., Hopper, J., Jenkins, M., Lindor, N.M., Newcomb, P.A., Gallinger, S., Conti, D., Schumacher, F., Casey, G., Giles, G.G., Pharoah, P., Peto, J., Cox, A., Swerdlow, A., Couch, F., Cunningham, J.M., Goode, E.L., Winham, S.J., Lambrechts, D., Fasching, P., Burwinkel, B., Brenner, H., Brauch, H., Chang-Claude, J., Salvesen, H.B., Kristensen, V., Darabi, H., Li, J., Liu, T., Lindblom, A., Hall, P., Echeverry de Polanco, M., Sans, M., Carracedo, A., Castellvi-Bel, S., Rojas-Martinez, A., Jr, A.S., Teixeira, M.R., Dunning, A.M., Dennis, J., Otton, G., Proietto, T., Holliday, E., Attia, J., Ashton, K., Scott, R.J., McEvoy, M., Dowdy, S.C., Fridley, B.L., Werner, H.M.J., Trovik, J., Njolstad, T.S., Tham, E., Mints, M., Runnebaum, I., Hillemanns, P., Doerk, T., Amant, F., Schrauwen, S., Hein, A., Beckmann, M.W., Ekici, A., Czene, K., Meindl, A., Bolla, M.K., Michailidou, K., Tyrer, J.P., Wang, Q., Ahmed, S., Healey, C.S., Shah, M., Annibali, D., Depreeuw, J., Al-Tassan, N.A., Harris, R., Meyer, B.F., Whiffin, N., Hosking, F.J., Kinnersley, B., Farrington, S.M., Timofeeva, M., Tenesa, A., Campbell, H., Haile, R.W., Hodgson, S., Carvajal-Carmona, L., Cheadle, J.P., Easton, D., Dunlop, M., Houlston, R., Spurdle, A., Tomlinson, I., and Other departments

Subjects
Male, CARCINOMA, MICROSATELLITE INSTABILITY, DNA-POLYMERASE, LOCI, MTHFR C677T, VARIANTS, LYNCH-SYNDROME, Article, BREAST-CANCER, Humans, Genetic Predisposition to Disease, Alleles, Adaptor Proteins, Signal Transducing, RISK, Homeodomain Proteins, Science & Technology, Polymorphism, Genetic, MUTATIONS, Intracellular Signaling Peptides and Proteins, Proteins, Endometrial Neoplasms, Neoplasm Proteins, Multidisciplinary Sciences, Repressor Proteins, Science & Technology - Other Topics, Female, Colorectal Neoplasms, Genome-Wide Association Study
Abstract

High-risk mutations in several genes predispose to both colorectal cancer (CRC) and endometrial cancer (EC). We therefore hypothesised that some lower-risk genetic variants might also predispose to both CRC and EC. Using CRC and EC genome-wide association series, totalling 13,265 cancer cases and 40,245 controls, we found that the protective allele [G] at one previously-identified CRC polymorphism, rs2736100 near TERT, was associated with EC risk (odds ratio (OR) = 1.08, P = 0.000167); this polymorphism influences the risk of several other cancers. A further CRC polymorphism near TERC also showed evidence of association with EC (OR = 0.92; P = 0.03). Overall, however, there was no good evidence that the set of CRC polymorphisms was associated with EC risk, and neither of two previously-reported EC polymorphisms was associated with CRC risk. A combined analysis revealed one genome-wide significant polymorphism, rs3184504, on chromosome 12q24 (OR = 1.10, P = 7.23 × 10(-9)) with shared effects on CRC and EC risk. This polymorphism, a missense variant in the gene SH2B3, is also associated with haematological and autoimmune disorders, suggesting that it influences cancer risk through the immune response. Another polymorphism, rs12970291 near gene TSHZ1, was associated with both CRC and EC (OR = 1.26, P = 4.82 × 10(-8)), with the alleles showing opposite effects on the risks of the two cancers. ispartof: Scientific Reports vol:5 pages:17369- ispartof: location:England status: published

Published
2015

40. Identification of novel genetic markers of breast cancer survival

Author

Guo, Q, Schmidt, Mk, Kraft, P, Canisius, S, Chen, C, Khan, S, Tyrer, J, Bolla, Mk, Wang, Q, Dennis, J, Michailidou, K, Lush, M, Kar, S, Beesley, J, Dunning, Am, Shah, M, Czene, K, Darabi, H, Eriksson, M, Lambrechts, D, Weltens, C, Leunen, K, Bojesen, Se, Nordestgaard, Bg, Nielsen, Sf, Flyger, H, Chang Claude, J, Rudolph, A, Seibold, P, Flesch Janys, D, Blomqvist, C, Aittomäki, K, Fagerholm, R, Muranen, Ta, Couch, Fj, Olson, Je, Vachon, C, Andrulis, Il, Knight, Ja, Glendon, G, Mulligan, Am, Broeks, A, Hogervorst, Fb, Haiman, Ca, Henderson, Be, Schumacher, F, Le Marchand, L, Hopper, Jl, Tsimiklis, H, Apicella, C, Southey, Mc, Cox, A, Cross, Ss, Reed, Mw, Giles, Gg, Milne, Rl, Mclean, C, Winqvist, R, Pylkäs, K, Jukkola Vuorinen, A, Grip, M, Hooning, Mj, Hollestelle, A, Martens, Jw, van den Ouweland, Am, Marme, F, Schneeweiss, A, Yang, R, Burwinkel, B, Figueroa, J, Chanock, Sj, Lissowska, J, Sawyer, Ej, Tomlinson, I, Kerin, Mj, Miller, N, Brenner, H, Dieffenbach, Ak, Arndt, V, Holleczek, B, Mannermaa, A, Kataja, V, Kosma, Vm, Hartikainen, Jm, Li, J, Brand, Js, Humphreys, K, Devilee, P, Tollenaar, Ra, Seynaeve, C, Radice, P, Peterlongo, P, Bonanni, B, Mariani, P, Fasching, Beckmann, Mw, Hein, A, Ekici, Ab, Chenevix Trench, G, Balleine, R, Kconfab, Investigators, Phillips, Ka, Benitez, J, Zamora, Mp, Arias Perez, Ji, Menéndez, P, Jakubowska, A, Lubinski, J, Jaworska Bieniek, K, Durda, K, Hamann, U, Kabisch, M, Ulmer, Hu, Rüdiger, T, Margolin, S, Kristensen, V, Nord, S, Evans, Dg, Abraham, Je, Earl, Hm, Hiller, L, Dunn, Ja, Bowden, S, Berg, C, Campa, Daniele, Diver, Wr, Gapstur, Sm, Gaudet, Mm, Hankinson, Se, Hoover, Rn, Hüsing, A, Kaaks, R, Machiela, Mj, Willett, W, Barrdahl, M, Canzian, F, Chin, Sf, Caldas, C, Hunter, Dj, Lindstrom, S, García Closas, M, Hall, P, Easton, Df, Eccles, Dm, Rahman, N, Nevanlinna, H, and Pharoah, P. d.

Subjects
GENOME-WIDE ASSOCIATION, SINGLE-NUCLEOTIDE POLYMORPHISMS, GENOTYPE IMPUTATION, PROGNOSIS, RISK, LOCI, CYCLOPHOSPHAMIDE, METAANALYSIS, PROGRESSION, EPIRUBICIN
Published
2015

41. Common non-synonymous SNPs associated with breast cancer susceptibility: findings from the Breast Cancer Association Consortium

Author

Milne, R.L., Burwinkel, B., Michailidou, K., Arias-Perez, J.I., Zamora, M.P., Menendez-Rodriguez, P., Hardisson, D., Mendiola, M., Gonzalez-Neira, A., Pita, G., Alonso, M.R., Dennis, J., Wang, Q., Bolla, M.K., Swerdlow, A., Ashworth, A., Orr, N., Schoemaker, M., Ko, Y.D., Brauch, H., Hamann, U., Andrulis, I.L., Knight, J.A., Glendon, G., Tchatchou, S., Matsuo, K., Ito, H., Iwata, H., Tajima, K., Li, J.M., Brand, J.S., Brenner, H., Dieffenbach, A.K., Arndt, V., Stegmaier, C., Lambrechts, D., Peuteman, G., Christiaens, M.R., Smeets, A., Jakubowska, A., Lubinski, J., Jaworska-Bieniek, K., Durda, K., Hartman, M., Hui, M., Lim, W.Y., Chan, C.W., Marme, F., Yang, R.X., Bugert, P., Lindblom, A., Margolin, S., Garcia-Closas, M., Chanock, S.J., Lissowska, J., Figueroa, J.D., Bojesen, S.E., Nordestgaard, B.G., Flyger, H., Hooning, M.J., Kriege, M., Ouweland, A.M.W. van den, Koppert, L.B., Fletcher, O., Johnson, N., Dos-Santos-Silva, I., Peto, J., Zheng, W., Deming-Halverson, S., Shrubsole, M.J., Long, J.R., Chang-Claude, J., Rudolph, A., Seibold, P., Flesch-Janys, D., Winqvist, R., Pylkas, K., Jukkola-Vuorinen, A., Grip, M., Cox, A., Cross, S.S., Reed, M.W.R., Schmidt, M.K., Broeks, A., Cornelissen, S., Braaf, L., Kang, D., Choi, J.Y., Park, S.K., Noh, D.Y., Simard, J., Dumont, M., Goldberg, M.S., Labreche, F., Fasching, P.A., Hein, A., Ekici, A.B., Beckmann, M.W., Radice, P., Peterlongo, P., Azzollini, J., Barile, M., Sawyer, E., Tomlinson, I., Kerin, M., Miller, N., Hopper, J.L., Schmidt, D.F., Makalic, E., Southey, M.C., Teo, S.H., Yip, C.H., Sivanandan, K., Tay, W.T., Shen, C.Y., Hsiung, C.N., Yu, J.C., Hou, M.F., Guenel, P., Truong, T., Sanchez, M., Mulot, C., Blot, W., Cai, Q.Y., Nevanlinna, H., Muranen, T.A., Aittomaki, K., Blomqvist, C., Wu, A.H., Tseng, C.C., Berg, D. van den, Stram, D.O., Bogdanova, N., Dork, T., Muir, K., Lophatananon, A., Stewart-Brown, S., Siriwanarangsan, P., Mannermaa, A., Kataja, V., Kosma, V.M., Hartikainen, J.M., Shu, X.O., Lu, W., Gao, Y.T., Zhang, B., Couch, F.J., Toland, A.E., Yannoukakos, D., Sangrajrang, S., McKay, J., Wang, X.S., Olson, J.E., Vachon, C., Purrington, K., Severi, G., Baglietto, L., Haiman, C.A., Henderson, B.E., Schumacher, F., Marchand, L. le, Devilee, P., Tollenaar, R.A.E.M., Seynaeve, C., Czene, K., Eriksson, M., Humphreys, K., Darabi, H., Ahmed, S., Shah, M., Pharoah, P.D.P., Hall, P., Giles, G.G., Benitez, J., Dunning, A.M., Chenevix-Trench, G., Easton, D.F., GENICA Network, kConFab Investigators, Australian Ovarian Canc Study Grp, TNBCC, Dennis, Joe [0000-0003-4591-1214], Wang, Jean [0000-0002-9139-0627], Pharoah, Paul [0000-0001-8494-732X], Dunning, Alison [0000-0001-6651-7166], Easton, Douglas [0000-0003-2444-3247], and Apollo - University of Cambridge Repository

Subjects
Adult, Ataxin-7, A Kinase Anchor Proteins, Breast Neoplasms, Nerve Tissue Proteins, Middle Aged, Protein Serine-Threonine Kinases, Polymorphism, Single Nucleotide, Cytoskeletal Proteins, Case-Control Studies, Humans, NIMA-Related Kinases, Female, Genetic Predisposition to Disease, health care economics and organizations, Alleles, Genome-Wide Association Study
Abstract

Candidate variant association studies have been largely unsuccessful in identifying common breast cancer susceptibility\ud variants, although most studies have been underpowered to detect associations of a realistic magnitude.\ud We assessed 41 common non-synonymous single-nucleotide polymorphisms (nsSNPs) for which\ud evidence of association with breast cancer risk had been previously reported. Case-control data were combined\ud from 38 studies of white European women (46 450 cases and 42 600 controls) and analyzed using unconditional\ud logistic regression. Strong evidence of association was observed for three nsSNPs: ATXN7-K264R at 3p21\ud [rs1053338, per allele OR 5 1.07, 95% confidence interval (CI) 5 1.04–1.10, P 5 2.9 3 1026\ud ], AKAP9-M463I at\ud 7q21 (rs6964587, OR 5 1.05, 95% CI 5 1.03–1.07, P 5 1.7 3 1026\ud ) and NEK10-L513S at 3p24 (rs10510592,\ud OR 5 1.10, 95% CI 5 1.07 –1.12, P 5 5.1 3 10217). The first two associations reached genome-wide statistical\ud significance in a combined analysis of available data, including independent data from nine genome-wide association\ud studies (GWASs): for ATXN7-K264R, OR 5 1.07 (95% CI 5 1.05–1.10, P 5 1.0 3 1028\ud ); for AKAP9-M463I,\ud OR 5 1.05 (95% CI 5 1.04–1.07, P 5 2.0 3 10210). Further analysis of other common variants in these two\ud regions suggested that intronic SNPs nearby are more strongly associated with disease risk. We have thus identified\ud a novel susceptibility locus at 3p21, and confirmed previous suggestive evidence that rs6964587 at 7q21 is\ud associated with risk. The third locus, rs10510592, is located in an established breast cancer susceptibility\ud region; the association was substantially attenuated after adjustment for the known GWAS hit. Thus, each of\ud the associated nsSNPs is likely to be a marker for another, non-coding, variant causally related to breast\ud cancer risk. Further fine-mapping and functional studies are required to identify the underlying risk-modifying\ud variants and the genes through which they act.

Published
2014

42. A large-scale assessment of two-way SNP interactions in breast cancer susceptibility using 46,450 cases and 42,461 controls from the breast cancer association consortium

Author

Rl, Milne, Herranz J, Michailidou K, Joe Dennis, Jp, Tyrer, Mp, Zamora, Ji, Arias-Perez, González-Neira A, Pita G, Alonso MR, Wang Q, Mk, Bolla, Czene K, Eriksson M, Humphreys K, Darabi H, Li J, Anton-Culver H, Sl, Neuhausen, Ziogas A, Ca, Clarke, Jl, Hopper, Gs, Dite, Apicella C, Mc, Southey, Chenevix-Trench G, kConFab Investigators, Australian Ovarian Cancer Study Group, Swerdlow A, Ashworth A, Orr N, Schoemaker M, Jakubowska A, Lubinski J, Jaworska-Bieniek K, Durda K, Il, Andrulis, Ja, Knight, Glendon G, Am, Mulligan, Se, Bojesen, Bg, Nordestgaard, Flyger H, Nevanlinna H, Ta, Muranen, Aittomäki K, Blomqvist C, Chang-Claude J, Rudolph A, Seibold P, Flesch-Janys D, Wang X, Je, Olson, Vachon C, Purrington K, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Am, Dunning, Shah M, Guénel P, Truong T, Sanchez M, Mulot C, Brenner H, Ak, Dieffenbach, Arndt V, Stegmaier C, Lindblom A, Margolin S, Hooning M, Hollestelle A, Collée M, Jager A, Cox A, Iw, Brock, Mw, Reed, Devilee P, Ra, Tollenaar, Seynaeve C, Ca, Haiman, Be, Henderson, Schumacher F, Le Marchand L, Simard J, Dumont M, Soucy P, Dörk T, Nv, Bogdanova, Hamann U, Försti A, Rüdiger T, Hu, Ulmer, Pa, Fasching, Häberle L, Ab, Ekici, Mw, Beckmann, Fletcher O, Johnson N, Id, Silva, Peto J, Radice P, Peterlongo P, Peissel B, Mariani P, Gg, Giles, Severi G, Baglietto L, Sawyer E, Tomlinson I, Kerin M, Miller N, Marme F, Burwinkel B, Mannermaa A, Kataja V, Vm, Kosma, Hartikainen J, Lambrechts D, Bt, Yesilyurt, Floris G, Leunen K, Gg, Alnæs, Kristensen V, Al, Børresen-Dale, García-Closas M, Sj, Chanock, Lissowska J, Jd, Figueroa, Mk, Schmidt, Broeks A, Verhoef S, Ej, Rutgers, Brauch H, Brüning T, Yd, Ko, Genica, The Network, Fj, Couch, Ae, Toland, Tnbcc, The, Yannoukakos D, Pd, Pharoah, Hall P, Benítez J, Malats N, and Df, Easton

Subjects
Australian Ovarian Cancer Study Group, Genetics & Heredity, Breast Neoplasms, Epistasis, Genetic, Biological Sciences, TNBCC, Polymorphism, Single Nucleotide, Medical and Health Sciences, Logistic Models, Case-Control Studies, kConFab Investigators, Humans, Genetic Predisposition to Disease, Female, GENICA Network, Genome-Wide Association Study
Abstract

Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70,917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46,450 breast cancer cases and 42,461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P < 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P < 10(-4)) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P < 10(-8). Results from the second analytic approach were consistent with those from the first (P > 10(-10)). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.

Published
2014

45. Introducing box-plate beam-to-column moment connections.

Author

Shishegaran, A., Rahimi, S., and Darabi, H.

Subjects
BOX beams, DUCTILITY, COMPOSITE construction, COMPRESSION loads, TENSILE strength
Abstract

Nowadays, using high-ductility structures in the construction and use of significant buildings is highly appreciated. To use more ductile structures, effort has been made in this research to introduce box-plate beam-to-column connections. They underwent hysteretic loading and it was found from their moment-rotation curves that the bending capacity and ductility of the box-plate connection were more than ordinary rigid connection, and those of the latter were more than those of the normal typical one. It was also shown that stress concentration in box-plate connections disappears over the top and bottom flange plates. [ABSTRACT FROM AUTHOR]

Published
2017
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46. Association of serum uric acid with high-sensitivity C-reactive protein in postmenopausal women.

Author

Raeisi, A., Ostovar, A., Vahdat, K., Rezaei, P., Darabi, H., Moshtaghi, D., and Nabipour, I.

Subjects
URIC acid, C-reactive protein, POSTMENOPAUSE, ENZYME-linked immunosorbent assay, LOGISTIC regression analysis, FASTING, HUMAN research subjects
Abstract

Objectives: To explore the independent correlation between serum uric acid and low-grade inflammation (measured by high-sensitivity C-reactive protein, hs-CRP) in postmenopausal women.Methods: A total of 378 healthy Iranian postmenopausal women were randomly selected in a population-based study. Circulating hs-CRP levels were measured by highly specific enzyme-linked immunosorbent assay method and an enzymatic calorimetric method was used to measure serum levels of uric acid. Pearson correlation coefficient, multiple linear regression and logistic regression models were used to analyze the association between uric acid and hs-CRP levels.Results: A statistically significant correlation was seen between serum levels of uric acid and log-transformed circulating hs-CRP (r = 0.25, p < 0.001). After adjustment for age and cardiovascular risk factors (according to NCEP ATP III criteria), circulating hs-CRP levels were significantly associated with serum uric acid levels (β = 0.20, p < 0.001). After adjustment for age and cardiovascular risk factors, hs-CRP levels ≥3 mg/l were significantly associated with higher uric acid levels (odds ratio =1.52, 95% confidence interval 1.18-1.96).Conclusion: Higher serum uric acid levels were positively and independently associated with circulating hs-CRP in healthy postmenopausal women. [ABSTRACT FROM AUTHOR]

Published
2017
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48. Integrated Analysis of Urban Landscape Fragmentation (Case Study: Historical-Religious City of Ray).

Author

Assar Khaniki, Z., Darabi, H., and Irani-Behbahani, H.

Abstract

Landscape fragmentation has threatened the landscape continuity of Ray which was maintained from prehistoric times until recent decades. From 19th century that Tehran sprawl growth affected Ray's landscape as a satellite city of Tehran, Ray experienced rapid landscape fragmentation and underwent many changes. In order to cope with the threat, the process of changes from landscape fragmentation should be studied. For this purpose, integrated approach was applied to assess landscape fragmentation. Landscape fragmentation is analyzed based on physical and quantitative evaluation using landscape metrics and perceptual and quantitative evaluation through an in-depth interview with natives. The results have cleared an image of the structural changes and also great change of people's perception during the time. Based on the results, Ray's landscape is structurally fragmented, but native do not perceive it. This is while people perceive landscape functional fragmentation. This inconsistent perception of landscape has caused the native's dissatisfaction about their living place. With the prepared image of landscape fragmentation in the City of Ray, city managers, designers, and planners will be able to deal with rapid changes and preserve landscape continuity of Ray. [ABSTRACT FROM AUTHOR]

Published
2015

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