Search

Your search keyword '"Bertrand, Kimberly A."' showing total 45 results
Start Over Author "Bertrand, Kimberly A." Language undetermined
45 results on '"Bertrand, Kimberly A."'

1. Polygenic risk scores for prediction of breast cancer risk in women of African ancestry: a cross-ancestry approach

Author

Gao, Guimin, Zhao, Fangyuan, Ahearn, Thomas U, Lunetta, Kathryn L, Troester, Melissa A, Du, Zhaohui, Ogundiran, Temidayo O, Ojengbede, Oladosu, Blot, William, Nathanson, Katherine L, Domchek, Susan M, Nemesure, Barbara, Hennis, Anselm, Ambs, Stefan, McClellan, Julian, Nie, Mark, Bertrand, Kimberly, Zirpoli, Gary, Yao, Song, Olshan, Andrew F, Bensen, Jeannette T, Bandera, Elisa V, Nyante, Sarah, Conti, David V, Press, Michael F, Ingles, Sue A, John, Esther M, Bernstein, Leslie, Hu, Jennifer J, Deming-Halverson, Sandra L, Chanock, Stephen J, Ziegler, Regina G, Rodriguez-Gil, Jorge L, Sucheston-Campbell, Lara E, Sandler, Dale P, Taylor, Jack A, Kitahara, Cari M, O’Brien, Katie M, Bolla, Manjeet K, Dennis, Joe, Dunning, Alison M, Easton, Douglas F, Michailidou, Kyriaki, Pharoah, Paul D P, Wang, Qin, Figueroa, Jonine, Biritwum, Richard, Adjei, Ernest, Wiafe, Seth, Ambrosone, Christine B, Zheng, Wei, Olopade, Olufunmilayo I, García-Closas, Montserrat, Palmer, Julie R, Haiman, Christopher A, and Huo, Dezheng

Subjects
Multifactorial Inheritance, Receptors, Estrogen/genetics, Breast Neoplasms, General Medicine, Breast Neoplasms/genetics, Receptors, Estrogen, Risk Factors, Genetics, Humans, Original Article, Female, Genetic Predisposition to Disease, Multifactorial Inheritance/genetics, Molecular Biology, Genetics (clinical), Genome-Wide Association Study
Abstract

Polygenic risk scores (PRSs) are useful for predicting breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remains relatively low. We aim to develop optimal PRSs for the prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in AA women. The AA dataset comprised 9235 cases and 10 184 controls from four genome-wide association study (GWAS) consortia and a GWAS study in Ghana. We randomly divided samples into training and validation sets. We built PRSs using individual-level AA data by a forward stepwise logistic regression and then developed joint PRSs that combined (1) the PRSs built in the AA training dataset and (2) a 313-variant PRS previously developed in women of European ancestry. PRSs were evaluated in the AA validation set. For overall breast cancer, the odds ratio per standard deviation of the joint PRS in the validation set was 1.34 [95% confidence interval (CI): 1.27–1.42] with the area under receiver operating characteristic curve (AUC) of 0.581. Compared with women with average risk (40th–60th PRS percentile), women in the top decile of the PRS had a 1.98-fold increased risk (95% CI: 1.63–2.39). For PRSs of ER-positive and ER-negative breast cancer, the AUCs were 0.608 and 0.576, respectively. Compared with existing methods, the proposed joint PRSs can improve prediction of breast cancer risk in AA women.

Published
2022

2. Polygenic risk scores for prediction of breast cancer risk in women of African ancestry: a cross-ancestry approach

Author

Gao, Guimin, Zhao, Fangyuan, Ahearn, Thomas U, Lunetta, Kathryn L, Troester, Melissa A, Du, Zhaohui, Ogundiran, Temidayo O, Ojengbede, Oladosu, Blot, William, Nathanson, Katherine L, Domchek, Susan M, Nemesure, Barbara, Hennis, Anselm, Ambs, Stefan, McClellan, Julian, Nie, Mark, Bertrand, Kimberly, Zirpoli, Gary, Yao, Song, Olshan, Andrew F, Bensen, Jeannette T, Bandera, Elisa V, Nyante, Sarah, Conti, David V, Press, Michael F, Ingles, Sue A, John, Esther M, Bernstein, Leslie, Hu, Jennifer J, Deming-Halverson, Sandra L, Chanock, Stephen J, Ziegler, Regina G, Rodriguez-Gil, Jorge L, Sucheston-Campbell, Lara E, Sandler, Dale P, Taylor, Jack A, Kitahara, Cari M, O'Brien, Katie M, Bolla, Manjeet K, Dennis, Joe, Dunning, Alison M, Easton, Douglas F, Michailidou, Kyriaki, Pharoah, Paul DP, Wang, Qin, Figueroa, Jonine, Biritwum, Richard, Adjei, Ernest, Wiafe, Seth, GBHS Study Team, Ambrosone, Christine B, Zheng, Wei, Olopade, Olufunmilayo I, García-Closas, Montserrat, Palmer, Julie R, Haiman, Christopher A, Huo, Dezheng, Dunning, Alison M [0000-0001-6651-7166], Huo, Dezheng [0000-0002-4041-1678], and Apollo - University of Cambridge Repository

Subjects
Multifactorial Inheritance, Receptors, Estrogen, Risk Factors, Humans, Breast Neoplasms, Female, Genetic Predisposition to Disease, Genome-Wide Association Study
Abstract

Polygenic risk scores (PRSs) are useful for predicting breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remains relatively low. We aim to develop optimal PRSs for the prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in AA women. The AA dataset comprised 9235 cases and 10 184 controls from four genome-wide association study (GWAS) consortia and a GWAS study in Ghana. We randomly divided samples into training and validation sets. We built PRSs using individual-level AA data by a forward stepwise logistic regression and then developed joint PRSs that combined (1) the PRSs built in the AA training dataset and (2) a 313-variant PRS previously developed in women of European ancestry. PRSs were evaluated in the AA validation set. For overall breast cancer, the odds ratio per standard deviation of the joint PRS in the validation set was 1.34 [95% confidence interval (CI): 1.27-1.42] with the area under receiver operating characteristic curve (AUC) of 0.581. Compared with women with average risk (40th-60th PRS percentile), women in the top decile of the PRS had a 1.98-fold increased risk (95% CI: 1.63-2.39). For PRSs of ER-positive and ER-negative breast cancer, the AUCs were 0.608 and 0.576, respectively. Compared with existing methods, the proposed joint PRSs can improve prediction of breast cancer risk in AA women.

Published
2022
Full Text
View/download PDF

3. Additional file 1 of The association of age at menarche and adult height with mammographic density in the International Consortium of Mammographic Density

Author

Ward, Sarah V., Burton, Anya, Tamimi, Rulla M., Pereira, Ana, Garmendia, Maria Luisa, Pollan, Marina, Boyd, Norman, dos-Santos-Silva, Isabel, Maskarinec, Gertraud, Perez-Gomez, Beatriz, Vachon, Celine, Miao, Hui, Lajous, Martín, López-Ridaura, Ruy, Bertrand, Kimberly, Kwong, Ava, Ursin, Giske, Lee, Eunjung, Ma, Huiyan, Vinnicombe, Sarah, Moss, Sue, Allen, Steve, Ndumia, Rose, Vinayak, Sudhir, Teo, Soo-Hwang, Mariapun, Shivaani, Peplonska, Beata, Bukowska-Damska, Agnieszka, Nagata, Chisato, Hopper, John, Giles, Graham, Ozmen, Vahit, Aribal, Mustafa Erkin, Schüz, Joachim, Van Gils, Carla H., Wanders, Johanna O. P., Sirous, Reza, Sirous, Mehri, Hipwell, John, Kim, Jisun, Lee, Jong Won, Dickens, Caroline, Hartman, Mikael, Chia, Kee-Seng, Scott, Christopher, Chiarelli, Anna M., Linton, Linda, Flugelman, Anath Arzee, Salem, Dorria, Kamal, Rasha, McCormack, Valerie, and Stone, Jennifer

Abstract

Additional file 1. Tables S1 and S2: Supplementary data providing results from sensitivity analyses of pooled models adjusted for a population-specific weight-for-height index instead of BMI

Published
2022
Full Text
View/download PDF

4. Additional file 1 of Neighborhood disadvantage and individual-level life stressors in relation to breast cancer incidence in US Black women

Author

Barber, Lauren E., Zirpoli, Gary R., Cozier, Yvette C., Rosenberg, Lynn, Petrick, Jessica L., Bertrand, Kimberly A., and Palmer, Julie R.

Abstract

Additional file 1: Table S1. Distributions of the factors that contribute to neighborhood SES and neighborhood concentrated disadvantage scores, at baseline in 1995.

Published
2021
Full Text
View/download PDF

5. Environmental radon exposure and breast cancer risk in the Nurses' Health Study II

Author

VoPham, Trang, DuPré, Natalie, Tamimi, Rulla M, James, Peter, Bertrand, Kimberly A, Vieira, Veronica, Laden, Francine, and Hart, Jaime E

Subjects
Adult, Ionizing radiation, Prevention, Incidence, Breast Neoplasms, Radiation Exposure, Toxicology, United States, Breast cancer, Radon, Risk Factors, Public Health and Health Services, Humans, Female, Prospective Studies, Cancer, Radioactive Pollutants
Abstract

BackgroundRadon and its decay products, a source of ionizing radiation, are primarily inhaled and can deliver a radiation dose to breast tissue, where they may continue to decay and emit DNA damage-inducing particles. Few studies have examined the relationship between radon and breast cancer.MethodsThe Nurses' Health Study II (NHSII) includes U.S. female registered nurses who completed biennial questionnaires since 1989. Self-reported breast cancer was confirmed from medical records. County-level radon exposures were linked with geocoded residential addresses updated throughout follow-up. Time-varying Cox regression models adjusted for established breast cancer risk factors were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs).ResultsFrom 1989 to 2013, 3966 invasive breast cancer cases occurred among 112,639 participants. Increasing radon exposure was not associated with breast cancer risk overall (adjusted HR comparing highest to lowest quintile=1.06, 95% CI: 0.94, 1.21, p for trend=0.30). However, women in the highest quintile of exposure (≥74.9Bq/m3) had a suggested elevated risk of ER-/PR- breast cancer compared to women in the lowest quintile (

Published
2017

6. Early Life Body Fatness, Serum Anti-Müllerian Hormone, and Breast Density in Young Adult Women

Author

Bertrand, Kimberly A, Baer, Heather J, Orav, E John, Klifa, Catherine, Kumar, Ajay, Hylton, Nola M, LeBlanc, Erin S, Snetselaar, Linda G, Van Horn, Linda, and Dorgan, Joanne F

Subjects
Adult, Anti-Mullerian Hormone, Adolescent, Epidemiology, Breast Neoplasms, Enzyme-Linked Immunosorbent Assay, Medical and Health Sciences, Body Mass Index, Young Adult, Risk Factors, Clinical Research, Breast Cancer, Humans, Obesity, Child, Breast Density, Nutrition, Cancer, Pediatric, Tumor, Prevention, Age Factors, Magnetic Resonance Imaging, Adipose Tissue, Female, Biomarkers, Follow-Up Studies
Abstract

BackgroundEmerging evidence suggests positive associations between serum anti-Müllerian hormone (AMH), a marker of ovarian function, and breast cancer risk. Body size at young ages may influence AMH levels, but few studies have examined this. Also, no studies have examined the relation of AMH levels with breast density, a strong predictor of breast cancer risk.MethodsWe examined associations of early life body fatness, AMH concentrations, and breast density among 172 women in the Dietary Intervention Study in Children (DISC). Height and weight were measured at baseline (ages 8-10) and throughout adolescence. Serum AMH concentrations and breast density were assessed at ages 25-29 at the DISC 2006 Follow-up visit. We used linear mixed effects models to quantify associations of AMH (dependent variable) with quartiles of age-specific youth body mass index (BMI) Z-scores (independent variable). We assessed cross-sectional associations of breast density (dependent variable) with AMH concentration (independent variable).ResultsNeither early life BMI nor current adult BMI was associated with AMH concentrations. There were no associations between AMH and percent or absolute dense breast volume. In contrast, women with higher AMH concentrations had significantly lower absolute nondense breast volume (Ptrend < 0.01).ConclusionsWe found no evidence that current or early life BMI influences AMH concentrations in later life. Women with higher concentrations of AMH had similar percent and absolute dense breast volume, but lower nondense volume.ImpactThese results suggest that AMH may be associated with lower absolute nondense breast volume; however, future prospective studies are needed to establish temporality. Cancer Epidemiol Biomarkers Prev; 25(7); 1151-7. ©2016 AACR.

Published
2016

7. Additional file 1: Table S1. of Mammographic texture and risk of breast cancer by tumor type and estrogen receptor status

Author

Malkov, Serghei, Shepherd, John, Scott, Christopher, Rulla Tamimi, Ma, Lin, Bertrand, Kimberly, Couch, Fergus, Jensen, Matthew, Mahmoudzadeh, Amir, Fan, Bo, Norman, Aaron, Brandt, Kathleen, V. Pankratz, Celine Vachon, and Kerlikowske, Karla

Abstract

Baseline characteristics of study population per study site. Table S2. Pearson correlation coefficient for top 15 significant features. Correlations calculated using case subjects. Gray and gray with line pattern highlight strength of positive and negative associations, respectively. (PDF 123 kb)

Published
2016
Full Text
View/download PDF

8. Additional file 4: of Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems

Author

Burton, Anya, Byrnes, Graham, Stone, Jennifer, Rulla Tamimi, Heine, John, Celine Vachon, Ozmen, Vahit, Pereira, Ana, Garmendia, Maria, Scott, Christopher, Hipwell, John, Dickens, Caroline, SchĂźz, Joachim, Aribal, Mustafa, Bertrand, Kimberly, Kwong, Ava, Giles, Graham, Hopper, John, GĂłmez, Beatriz PĂŠrez, PollĂĄn, Marina, Soo-Hwang Teo, Shivaani Mariapun, Taib, Nur, MartĂ­N Lajous, Lopez-Riduara, Ruy, Rice, Megan, Romieu, Isabelle, Anath Flugelman, Giske Ursin, Qureshi, Samera, Huiyan Ma, Eunjung Lee, Sirous, Reza, Mehri Sirous, Lee, Jong, Jisun Kim, Dorria Salem, Kamal, Rasha, Hartman, Mikael, Miao, Hui, Kee-Seng Chia, Nagata, Chisato, Vinayak, Sudhir, Ndumia, Rose, Gils, Carla Van, Wanders, Johanna, Peplonska, Beata, Bukowska, Agnieszka, Allen, Steve, Vinnicombe, Sarah, Moss, Sue, Chiarelli, Anna, Linton, Linda, Maskarinec, Gertraud, Yaffe, Martin, Boyd, Norman, Dos-Santos-Silva, Isabel, and McCormack, Valerie

Abstract

is Table S4 presenting mean differences in MD measures between processed images and the corresponding raw digital image, by percent density and breast area categories. (DOC 30 kb)

Published
2016
Full Text
View/download PDF

9. Additional file 1: of Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems

Author

Burton, Anya, Byrnes, Graham, Stone, Jennifer, Rulla Tamimi, Heine, John, Celine Vachon, Ozmen, Vahit, Pereira, Ana, Garmendia, Maria, Scott, Christopher, Hipwell, John, Dickens, Caroline, Schüz, Joachim, Aribal, Mustafa, Bertrand, Kimberly, Kwong, Ava, Giles, Graham, Hopper, John, Gómez, Beatriz Pérez, Pollán, Marina, Soo-Hwang Teo, Shivaani Mariapun, Taib, Nur, Lajous, Martín, Lopez-Riduara, Ruy, Rice, Megan, Romieu, Isabelle, Anath Flugelman, Giske Ursin, Qureshi, Samera, Huiyan Ma, Eunjung Lee, Sirous, Reza, Mehri Sirous, Lee, Jong, Jisun Kim, Dorria Salem, Kamal, Rasha, Hartman, Mikael, Miao, Hui, Kee-Seng Chia, Nagata, Chisato, Vinayak, Sudhir, Ndumia, Rose, Gils, Carla Van, Wanders, Johanna, Peplonska, Beata, Bukowska, Agnieszka, Allen, Steve, Vinnicombe, Sarah, Moss, Sue, Chiarelli, Anna, Linton, Linda, Maskarinec, Gertraud, Yaffe, Martin, Boyd, Norman, Dos-Santos-Silva, Isabel, and McCormack, Valerie

Abstract

is Table S1 presenting percent density, dense area and total breast area in raw–processed image pairs and in SFM–processed digital image pairs, by reader. (DOC 33 kb)

Published
2016
Full Text
View/download PDF

10. Additional file 1: of Spatiotemporal exposure modeling of ambient erythemal ultraviolet radiation

Author

VoPham, Trang, Hart, Jaime, Bertrand, Kimberly, Zhibin Sun, Rulla Tamimi, and Laden, Francine

Abstract

Supplemental tables for UVMRP monitoring stations, regional linear mixed-effects regression models, model goodness-of-fit, validation results by UVMRP station, coherence property analysis, and yearly NASA grid-level July UVEry descriptive statistics. (DOCX 81 kb)

Published
2016
Full Text
View/download PDF

11. Additional file 3: of Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems

Author

Burton, Anya, Byrnes, Graham, Stone, Jennifer, Rulla Tamimi, Heine, John, Celine Vachon, Ozmen, Vahit, Pereira, Ana, Garmendia, Maria, Scott, Christopher, Hipwell, John, Dickens, Caroline, SchĂźz, Joachim, Aribal, Mustafa, Bertrand, Kimberly, Kwong, Ava, Giles, Graham, Hopper, John, GĂłmez, Beatriz PĂŠrez, PollĂĄn, Marina, Soo-Hwang Teo, Shivaani Mariapun, Taib, Nur, MartĂ­N Lajous, Lopez-Riduara, Ruy, Rice, Megan, Romieu, Isabelle, Anath Flugelman, Giske Ursin, Qureshi, Samera, Huiyan Ma, Eunjung Lee, Sirous, Reza, Mehri Sirous, Lee, Jong, Jisun Kim, Dorria Salem, Kamal, Rasha, Hartman, Mikael, Miao, Hui, Kee-Seng Chia, Nagata, Chisato, Vinayak, Sudhir, Ndumia, Rose, Gils, Carla Van, Wanders, Johanna, Peplonska, Beata, Bukowska, Agnieszka, Allen, Steve, Vinnicombe, Sarah, Moss, Sue, Chiarelli, Anna, Linton, Linda, Maskarinec, Gertraud, Yaffe, Martin, Boyd, Norman, Dos-Santos-Silva, Isabel, and McCormack, Valerie

Abstract

is Table S3 presenting correlation of MD measures in inter-reader repeats. (DOC 29 kb)

Published
2016
Full Text
View/download PDF

12. Additional file 7: of Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems

Author

Burton, Anya, Byrnes, Graham, Stone, Jennifer, Rulla Tamimi, Heine, John, Celine Vachon, Ozmen, Vahit, Pereira, Ana, Garmendia, Maria, Scott, Christopher, Hipwell, John, Dickens, Caroline, SchĂźz, Joachim, Aribal, Mustafa, Bertrand, Kimberly, Kwong, Ava, Giles, Graham, Hopper, John, GĂłmez, Beatriz PĂŠrez, PollĂĄn, Marina, Soo-Hwang Teo, Shivaani Mariapun, Taib, Nur, MartĂ­N Lajous, Lopez-Riduara, Ruy, Rice, Megan, Romieu, Isabelle, Anath Flugelman, Giske Ursin, Qureshi, Samera, Huiyan Ma, Eunjung Lee, Sirous, Reza, Mehri Sirous, Lee, Jong, Jisun Kim, Dorria Salem, Kamal, Rasha, Hartman, Mikael, Miao, Hui, Kee-Seng Chia, Nagata, Chisato, Vinayak, Sudhir, Ndumia, Rose, Gils, Carla Van, Wanders, Johanna, Peplonska, Beata, Bukowska, Agnieszka, Allen, Steve, Vinnicombe, Sarah, Moss, Sue, Chiarelli, Anna, Linton, Linda, Maskarinec, Gertraud, Yaffe, Martin, Boyd, Norman, Dos-Santos-Silva, Isabel, and McCormack, Valerie

Abstract

is Information 1 showing calibration equations for the conversion of raw vDA to processed vDA, and Information 2 showing calibration equations for the conversion of processed vDA to raw vDA. (DOC 41 kb)

Published
2016
Full Text
View/download PDF

13. Additional file 2: of Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems

Author

Burton, Anya, Byrnes, Graham, Stone, Jennifer, Rulla Tamimi, Heine, John, Celine Vachon, Ozmen, Vahit, Pereira, Ana, Garmendia, Maria, Scott, Christopher, Hipwell, John, Dickens, Caroline, SchĂźz, Joachim, Aribal, Mustafa, Bertrand, Kimberly, Kwong, Ava, Giles, Graham, Hopper, John, GĂłmez, Beatriz PĂŠrez, PollĂĄn, Marina, Soo-Hwang Teo, Shivaani Mariapun, Taib, Nur, MartĂ­N Lajous, Lopez-Riduara, Ruy, Rice, Megan, Romieu, Isabelle, Anath Flugelman, Giske Ursin, Qureshi, Samera, Huiyan Ma, Eunjung Lee, Sirous, Reza, Mehri Sirous, Lee, Jong, Jisun Kim, Dorria Salem, Kamal, Rasha, Hartman, Mikael, Miao, Hui, Kee-Seng Chia, Nagata, Chisato, Vinayak, Sudhir, Ndumia, Rose, Gils, Carla Van, Wanders, Johanna, Peplonska, Beata, Bukowska, Agnieszka, Allen, Steve, Vinnicombe, Sarah, Moss, Sue, Chiarelli, Anna, Linton, Linda, Maskarinec, Gertraud, Yaffe, Martin, Boyd, Norman, Dos-Santos-Silva, Isabel, and McCormack, Valerie

Abstract

is Table S2 presenting mean MD measures of inter-reader repeats, by reader and image type. (DOC 29 kb)

Published
2016
Full Text
View/download PDF

14. Additional file 6: of Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems

Author

Burton, Anya, Byrnes, Graham, Stone, Jennifer, Rulla Tamimi, Heine, John, Celine Vachon, Ozmen, Vahit, Pereira, Ana, Garmendia, Maria, Scott, Christopher, Hipwell, John, Dickens, Caroline, Schüz, Joachim, Aribal, Mustafa, Bertrand, Kimberly, Kwong, Ava, Giles, Graham, Hopper, John, Gómez, Beatriz Pérez, Pollán, Marina, Soo-Hwang Teo, Shivaani Mariapun, Taib, Nur, Lajous, Martín, Lopez-Riduara, Ruy, Rice, Megan, Romieu, Isabelle, Anath Flugelman, Giske Ursin, Qureshi, Samera, Huiyan Ma, Eunjung Lee, Sirous, Reza, Mehri Sirous, Lee, Jong, Jisun Kim, Dorria Salem, Kamal, Rasha, Hartman, Mikael, Miao, Hui, Kee-Seng Chia, Nagata, Chisato, Vinayak, Sudhir, Ndumia, Rose, Gils, Carla Van, Wanders, Johanna, Peplonska, Beata, Bukowska, Agnieszka, Allen, Steve, Vinnicombe, Sarah, Moss, Sue, Chiarelli, Anna, Linton, Linda, Maskarinec, Gertraud, Yaffe, Martin, Boyd, Norman, Dos-Santos-Silva, Isabel, and McCormack, Valerie

Abstract

is Figure S2 showing Bland–Altman plots for within-system and within-reader standardized vDA measures. (DOCX 79 kb)

Published
2016
Full Text
View/download PDF

15. Additional file 5: of Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems

Author

Burton, Anya, Byrnes, Graham, Stone, Jennifer, Rulla Tamimi, Heine, John, Celine Vachon, Ozmen, Vahit, Pereira, Ana, Garmendia, Maria, Scott, Christopher, Hipwell, John, Dickens, Caroline, Schüz, Joachim, Aribal, Mustafa, Bertrand, Kimberly, Kwong, Ava, Giles, Graham, Hopper, John, Gómez, Beatriz Pérez, Pollán, Marina, Soo-Hwang Teo, Shivaani Mariapun, Taib, Nur, Lajous, Martín, Lopez-Riduara, Ruy, Rice, Megan, Romieu, Isabelle, Anath Flugelman, Giske Ursin, Qureshi, Samera, Huiyan Ma, Eunjung Lee, Sirous, Reza, Mehri Sirous, Lee, Jong, Jisun Kim, Dorria Salem, Kamal, Rasha, Hartman, Mikael, Miao, Hui, Kee-Seng Chia, Nagata, Chisato, Vinayak, Sudhir, Ndumia, Rose, Gils, Carla Van, Wanders, Johanna, Peplonska, Beata, Bukowska, Agnieszka, Allen, Steve, Vinnicombe, Sarah, Moss, Sue, Chiarelli, Anna, Linton, Linda, Maskarinec, Gertraud, Yaffe, Martin, Boyd, Norman, Dos-Santos-Silva, Isabel, and McCormack, Valerie

Abstract

is Figure S1 showing Bland–Altman plots for vMD measures, by mammography system and reader for: (A) percent mammographic density, (B) dense area and (C) breast area. Y axes to the same scale for comparisons. (DOCX 138 kb)

Published
2016
Full Text
View/download PDF

16. Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for Thirteen Cancer Types

Author

Sampson, Joshua N, Wheeler, William A, Yeager, Meredith, Panagiotou, Orestis, Wang, Zhaoming, Berndt, Sonja I, Lan, Qing, Abnet, Christian C, Amundadottir, Laufey T, Figueroa, Jonine D, Landi, Maria Teresa, Mirabello, Lisa, Savage, Sharon A, Taylor, Philip R, De Vivo, Immaculata, McGlynn, Katherine A, Purdue, Mark P, Rajaraman, Preetha, Adami, Hans-Olov, Ahlbom, Anders, Albanes, Demetrius, Amary, Maria Fernanda, An, She-Juan, Andersson, Ulrika, Andriole, Gerald, Andrulis, Irene L, Angelucci, Emanuele, Ansell, Stephen M, Arici, Cecilia, Armstrong, Bruce K, Arslan, Alan A, Austin, Melissa A, Baris, Dalsu, Barkauskas, Donald A, Bassig, Bryan A, Becker, Nikolaus, Benavente, Yolanda, Benhamou, Simone, Berg, Christine, Van Den Berg, David, Bernstein, Leslie, Bertrand, Kimberly A, Birmann, Brenda M, Black, Amanda, Boeing, Heiner, Boffetta, Paolo, Boutron-Ruault, Marie-Christine, Bracci, Paige M, Brinton, Louise, Brooks-Wilson, Angela R, Bueno-de-Mesquita, H Bas, Burdett, Laurie, Buring, Julie, Butler, Mary Ann, Cai, Qiuyin, Cancel-Tassin, Geraldine, Canzian, Federico, Carrato, Alfredo, Carreon, Tania, Carta, Angela, Chan, John KC, Chang, Ellen T, Chang, Gee-Chen, Chang, I-Shou, Chang, Jiang, Chang-Claude, Jenny, Chen, Chien-Jen, Chen, Chih-Yi, Chen, Chu, Chen, Chung-Hsing, Chen, Constance, Chen, Hongyan, Chen, Kexin, Chen, Kuan-Yu, Chen, Kun-Chieh, Chen, Ying, Chen, Ying-Hsiang, Chen, Yi-Song, Chen, Yuh-Min, Chien, Li-Hsin, Chirlaque, María-Dolores, Choi, Jin Eun, Choi, Yi Young, Chow, Wong-Ho, Chung, Charles C, Clavel, Jacqueline, Clavel-Chapelon, Françoise, Cocco, Pierluigi, Colt, Joanne S, Comperat, Eva, Conde, Lucia, Connors, Joseph M, Conti, David, Cortessis, Victoria K, Cotterchio, Michelle, Cozen, Wendy, Crouch, Simon, Crous-Bou, Marta, Cussenot, Olivier, and Davis, Faith G

Subjects
Adult, Asian Continental Ancestry Group, Male, Lung Neoplasms, Lymphoma, European Continental Ancestry Group, Oncology and Carcinogenesis, Bone Neoplasms, Testicular Neoplasms, Neoplasms, Large B-Cell, Humans, Genetic Predisposition to Disease, Oncology & Carcinogenesis, Polymorphism, Chronic, Aged, Osteosarcoma, Leukemia, Smoking, B-Cell, Single Nucleotide, Middle Aged, Diffuse, Kidney Neoplasms, Lymphocytic, Urinary Bladder Neoplasms, Tissue Array Analysis, Female, Genome-Wide Association Study
Abstract

BackgroundStudies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites.MethodsBetween 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers.ResultsGWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl (2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE =0.18), and bladder and lung (ρ = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures.ConclusionOur results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.

Published
2015

17. Dense and nondense mammographic area and risk of breast cancer by age and tumor characteristics

Author

Bertrand, Kimberly A, Scott, Christopher G, Tamimi, Rulla M, Jensen, Matthew R, Pankratz, V Shane, Norman, Aaron D, Visscher, Daniel W, Couch, Fergus J, Shepherd, John, Chen, Yunn-Yi, Fan, Bo, Wu, Fang-Fang, Ma, Lin, Beck, Andrew H, Cummings, Steven R, Kerlikowske, Karla, and Vachon, Celine M

Subjects
Adult, Aging, Epidemiology, Age Factors, Breast Neoplasms, Middle Aged, Mammary Glands, Estrogen, Medical and Health Sciences, Radiography, Young Adult, ErbB-2, Risk Factors, Clinical Research, Receptors, Breast Cancer, Humans, Female, Human, Receptor, Breast Density, Cancer
Abstract

BackgroundMammographic density (MD) is a strong breast cancer risk factor. We previously reported associations of percent mammographic density (PMD) with larger and node-positive tumors across all ages, and estrogen receptor (ER)-negative status among women ages

Published
2015

18. A genome-wide association study of marginal zone lymphoma shows association to the HLA region

Author

Vijai, Joseph, Wang, Zhaoming, Berndt, Sonja I, Skibola, Christine F, Slager, Susan L, de Sanjose, Silvia, Melbye, Mads, Glimelius, Bengt, Bracci, Paige M, Conde, Lucia, Birmann, Brenda M, Wang, Sophia S, Brooks-Wilson, Angela R, Lan, Qing, de Bakker, Paul IW, Vermeulen, Roel CH, Portlock, Carol, Ansell, Stephen M, Link, Brian K, Riby, Jacques, North, Kari E, Gu, Jian, Hjalgrim, Henrik, Cozen, Wendy, Becker, Nikolaus, Teras, Lauren R, Spinelli, John J, Turner, Jenny, Zhang, Yawei, Purdue, Mark P, Giles, Graham G, Kelly, Rachel S, Zeleniuch-Jacquotte, Anne, Ennas, Maria Grazia, Monnereau, Alain, Bertrand, Kimberly A, Albanes, Demetrius, Lightfoot, Tracy, Yeager, Meredith, Chung, Charles C, Burdett, Laurie, Hutchinson, Amy, Lawrence, Charles, Montalvan, Rebecca, Liang, Liming, Huang, Jinyan, Ma, Baoshan, Villano, Danylo J, Maria, Ann, Corines, Marina, Thomas, Tinu, Novak, Anne J, Dogan, Ahmet, Liebow, Mark, Thompson, Carrie A, Witzig, Thomas E, Habermann, Thomas M, Weiner, George J, Smith, Martyn T, Holly, Elizabeth A, Jackson, Rebecca D, Tinker, Lesley F, Ye, Yuanqing, Adami, Hans-Olov, Smedby, Karin E, De Roos, Anneclaire J, Hartge, Patricia, Morton, Lindsay M, Severson, Richard K, Benavente, Yolanda, Boffetta, Paolo, Brennan, Paul, Foretova, Lenka, Maynadie, Marc, McKay, James, Staines, Anthony, Diver, W Ryan, Vajdic, Claire M, Armstrong, Bruce K, Kricker, Anne, Zheng, Tongzhang, Holford, Theodore R, Severi, Gianluca, Vineis, Paolo, Ferri, Giovanni M, Ricco, Rosalia, Miligi, Lucia, Clavel, Jacqueline, Giovannucci, Edward, Kraft, Peter, Virtamo, Jarmo, Smith, Alex, Kane, Eleanor, Roman, Eve, Chiu, Brian CH, Fraumeni, Joseph F, Wu, Xifeng, Cerhan, James R, Offit, Kenneth, and Chanock, Stephen J

Subjects
Membrane Glycoproteins, Genotype, Lymphoma, Butyrophilins, European Continental Ancestry Group, Human Genome, B-Cell, Computational Biology, Marginal Zone, Single Nucleotide, Hematology, White People, Major Histocompatibility Complex, Rare Diseases, Genetics, Humans, 2.1 Biological and endogenous factors, Polymorphism, Aetiology, Genome-Wide Association Study, Cancer
Abstract

Marginal zone lymphoma (MZL) is the third most common subtype of B-cell non-Hodgkin lymphoma. Here we perform a two-stage GWAS of 1,281 MZL cases and 7,127 controls of European ancestry and identify two independent loci near BTNL2 (rs9461741, P=3.95 × 10(-15)) and HLA-B (rs2922994, P=2.43 × 10(-9)) in the HLA region significantly associated with MZL risk. This is the first evidence that genetic variation in the major histocompatibility complex influences MZL susceptibility.

Published
2015

19. Genome-wide association study identifies multiple susceptibility loci for diffuse large B cell lymphoma

Author

Cerhan, James R, Berndt, Sonja I, Vijai, Joseph, Ghesquières, Hervé, McKay, James, Wang, Sophia S, Wang, Zhaoming, Yeager, Meredith, Conde, Lucia, de Bakker, Paul IW, Nieters, Alexandra, Cox, David, Burdett, Laurie, Monnereau, Alain, Flowers, Christopher R, De Roos, Anneclaire J, Brooks-Wilson, Angela R, Lan, Qing, Severi, Gianluca, Melbye, Mads, Gu, Jian, Jackson, Rebecca D, Kane, Eleanor, Teras, Lauren R, Purdue, Mark P, Vajdic, Claire M, Spinelli, John J, Giles, Graham G, Albanes, Demetrius, Kelly, Rachel S, Zucca, Mariagrazia, Bertrand, Kimberly A, Zeleniuch-Jacquotte, Anne, Lawrence, Charles, Hutchinson, Amy, Zhi, Degui, Habermann, Thomas M, Link, Brian K, Novak, Anne J, Dogan, Ahmet, Asmann, Yan W, Liebow, Mark, Thompson, Carrie A, Ansell, Stephen M, Witzig, Thomas E, Weiner, George J, Veron, Amelie S, Zelenika, Diana, Tilly, Hervé, Haioun, Corinne, Molina, Thierry Jo, Hjalgrim, Henrik, Glimelius, Bengt, Adami, Hans-Olov, Bracci, Paige M, Riby, Jacques, Smith, Martyn T, Holly, Elizabeth A, Cozen, Wendy, Hartge, Patricia, Morton, Lindsay M, Severson, Richard K, Tinker, Lesley F, North, Kari E, Becker, Nikolaus, Benavente, Yolanda, Boffetta, Paolo, Brennan, Paul, Foretova, Lenka, Maynadie, Marc, Staines, Anthony, Lightfoot, Tracy, Crouch, Simon, Smith, Alex, Roman, Eve, Diver, W Ryan, Offit, Kenneth, Zelenetz, Andrew, Klein, Robert J, Villano, Danylo J, Zheng, Tongzhang, Zhang, Yawei, Holford, Theodore R, Kricker, Anne, Turner, Jenny, Southey, Melissa C, Clavel, Jacqueline, Virtamo, Jarmo, Weinstein, Stephanie, Riboli, Elio, Vineis, Paolo, Kaaks, Rudolph, Trichopoulos, Dimitrios, Vermeulen, Roel CH, Boeing, Heiner, Tjonneland, Anne, Angelucci, Emanuele, Di Lollo, Simonetta, Rais, Marco, and Birmann, Brenda M

Subjects
Likelihood Functions, Genotype, Lymphoma, Quantitative Trait Loci, Human Genome, Chromosome Mapping, Computational Biology, Single Nucleotide, Hematology, Biological Sciences, Diffuse, Medical and Health Sciences, White People, Rare Diseases, Genetic Loci, Large B-Cell, Genetics, Humans, 2.1 Biological and endogenous factors, Genetic Predisposition to Disease, Polymorphism, Aetiology, Genome-Wide Association Study, Cancer, Developmental Biology
Abstract

Diffuse large B cell lymphoma (DLBCL) is the most common lymphoma subtype and is clinically aggressive. To identify genetic susceptibility loci for DLBCL, we conducted a meta-analysis of 3 new genome-wide association studies (GWAS) and 1 previous scan, totaling 3,857 cases and 7,666 controls of European ancestry, with additional genotyping of 9 promising SNPs in 1,359 cases and 4,557 controls. In our multi-stage analysis, five independent SNPs in four loci achieved genome-wide significance marked by rs116446171 at 6p25.3 (EXOC2; P = 2.33 × 10(-21)), rs2523607 at 6p21.33 (HLA-B; P = 2.40 × 10(-10)), rs79480871 at 2p23.3 (NCOA1; P = 4.23 × 10(-8)) and two independent SNPs, rs13255292 and rs4733601, at 8q24.21 (PVT1; P = 9.98 × 10(-13) and 3.63 × 10(-11), respectively). These data provide substantial new evidence for genetic susceptibility to this B cell malignancy and point to pathways involved in immune recognition and immune function in the pathogenesis of DLBCL.

Published
2014

20. Genome-wide association study identifies multiple susceptibility loci for diffuse large B cell lymphoma

Author

Cerhan, James R, Berndt, Sonja I, Vijai, Joseph, Ghesquières, Hervé, McKay, James, Wang, Sophia S, Wang, Zhaoming, Yeager, Meredith, Conde, Lucia, de Bakker, Paul IW, Nieters, Alexandra, Cox, David, Burdett, Laurie, Monnereau, Alain, Flowers, Christopher R, De Roos, Anneclaire J, Brooks-Wilson, Angela R, Lan, Qing, Severi, Gianluca, Melbye, Mads, Gu, Jian, Jackson, Rebecca D, Kane, Eleanor, Teras, Lauren R, Purdue, Mark P, Vajdic, Claire M, Spinelli, John J, Giles, Graham G, Albanes, Demetrius, Kelly, Rachel S, Zucca, Mariagrazia, Bertrand, Kimberly A, Zeleniuch-Jacquotte, Anne, Lawrence, Charles, Hutchinson, Amy, Zhi, Degui, Habermann, Thomas M, Link, Brian K, Novak, Anne J, Dogan, Ahmet, Asmann, Yan W, Liebow, Mark, Thompson, Carrie A, Ansell, Stephen M, Witzig, Thomas E, Weiner, George J, Veron, Amelie S, Zelenika, Diana, Tilly, Hervé, Haioun, Corinne, Molina, Thierry Jo, Hjalgrim, Henrik, Glimelius, Bengt, Adami, Hans-Olov, Bracci, Paige M, Riby, Jacques, Smith, Martyn T, Holly, Elizabeth A, Cozen, Wendy, Hartge, Patricia, Morton, Lindsay M, Severson, Richard K, Tinker, Lesley F, North, Kari E, Becker, Nikolaus, Benavente, Yolanda, Boffetta, Paolo, Brennan, Paul, Foretova, Lenka, Maynadie, Marc, Staines, Anthony, Lightfoot, Tracy, Crouch, Simon, Smith, Alex, Roman, Eve, Diver, W Ryan, Offit, Kenneth, Zelenetz, Andrew, Klein, Robert J, Villano, Danylo J, Zheng, Tongzhang, Zhang, Yawei, Holford, Theodore R, Kricker, Anne, Turner, Jenny, Southey, Melissa C, Clavel, Jacqueline, Virtamo, Jarmo, Weinstein, Stephanie, Riboli, Elio, Vineis, Paolo, Kaaks, Rudolph, Trichopoulos, Dimitrios, Vermeulen, Roel CH, Boeing, Heiner, Tjonneland, Anne, Angelucci, Emanuele, Di Lollo, Simonetta, Rais, Marco, and Birmann, Brenda M

Subjects
Likelihood Functions, Genotype, Lymphoma, Quantitative Trait Loci, European Continental Ancestry Group, Chromosome Mapping, Computational Biology, Single Nucleotide, Biological Sciences, Diffuse, Medical and Health Sciences, Genetic Loci, Large B-Cell, Humans, Genetic Predisposition to Disease, Polymorphism, Genome-Wide Association Study, Developmental Biology
Abstract

Diffuse large B cell lymphoma (DLBCL) is the most common lymphoma subtype and is clinically aggressive. To identify genetic susceptibility loci for DLBCL, we conducted a meta-analysis of 3 new genome-wide association studies (GWAS) and 1 previous scan, totaling 3,857 cases and 7,666 controls of European ancestry, with additional genotyping of 9 promising SNPs in 1,359 cases and 4,557 controls. In our multi-stage analysis, five independent SNPs in four loci achieved genome-wide significance marked by rs116446171 at 6p25.3 (EXOC2; P = 2.33 × 10(-21)), rs2523607 at 6p21.33 (HLA-B; P = 2.40 × 10(-10)), rs79480871 at 2p23.3 (NCOA1; P = 4.23 × 10(-8)) and two independent SNPs, rs13255292 and rs4733601, at 8q24.21 (PVT1; P = 9.98 × 10(-13) and 3.63 × 10(-11), respectively). These data provide substantial new evidence for genetic susceptibility to this B cell malignancy and point to pathways involved in immune recognition and immune function in the pathogenesis of DLBCL.

Published
2014

21. Genome-wide association study identifies five susceptibility loci for follicular lymphoma outside the HLA region

Author

Skibola, Christine F, Berndt, Sonja I, Vijai, Joseph, Conde, Lucia, Wang, Zhaoming, Yeager, Meredith, de Bakker, Paul IW, Birmann, Brenda M, Vajdic, Claire M, Foo, Jia-Nee, Bracci, Paige M, Vermeulen, Roel CH, Slager, Susan L, de Sanjose, Silvia, Wang, Sophia S, Linet, Martha S, Salles, Gilles, Lan, Qing, Severi, Gianluca, Hjalgrim, Henrik, Lightfoot, Tracy, Melbye, Mads, Gu, Jian, Ghesquières, Hervé, Link, Brian K, Morton, Lindsay M, Holly, Elizabeth A, Smith, Alex, Tinker, Lesley F, Teras, Lauren R, Kricker, Anne, Becker, Nikolaus, Purdue, Mark P, Spinelli, John J, Zhang, Yawei, Giles, Graham G, Vineis, Paolo, Monnereau, Alain, Bertrand, Kimberly A, Albanes, Demetrius, Zeleniuch-Jacquotte, Anne, Gabbas, Attilio, Chung, Charles C, Burdett, Laurie, Hutchinson, Amy, Lawrence, Charles, Montalvan, Rebecca, Liang, Liming, Huang, Jinyan, Ma, Baoshan, Liu, Jianjun, Adami, Hans-Olov, Glimelius, Bengt, Ye, Yuanqing, Nowakowski, Grzegorz S, Dogan, Ahmet, Thompson, Carrie A, Habermann, Thomas M, Novak, Anne J, Liebow, Mark, Witzig, Thomas E, Weiner, George J, Schenk, Maryjean, Hartge, Patricia, De Roos, Anneclaire J, Cozen, Wendy, Zhi, Degui, Akers, Nicholas K, Riby, Jacques, Smith, Martyn T, Lacher, Mortimer, Villano, Danylo J, Maria, Ann, Roman, Eve, Kane, Eleanor, Jackson, Rebecca D, North, Kari E, Diver, W Ryan, Turner, Jenny, Armstrong, Bruce K, Benavente, Yolanda, Boffetta, Paolo, Brennan, Paul, Foretova, Lenka, Maynadie, Marc, Staines, Anthony, McKay, James, Brooks-Wilson, Angela R, Zheng, Tongzhang, Holford, Theodore R, Chamosa, Saioa, Kaaks, Rudolph, Kelly, Rachel S, Ohlsson, Bodil, Travis, Ruth C, Weiderpass, Elisabete, Clavel, Jacqueline, Giovannucci, Edward, Kraft, Peter, and Virtamo, Jarmo

Subjects
Lymphoma, Medical and Health Sciences, Chromosomes, Rare Diseases, HLA Antigens, Clinical Research, Genetics, Humans, 2.1 Biological and endogenous factors, Genetic Predisposition to Disease, Polymorphism, Aetiology, Alleles, Cancer, Genetics & Heredity, Tumor, Human Genome, Follicular, Single Nucleotide, Hematology, Biological Sciences, Haplotypes, Case-Control Studies, Biomarkers, Human, Genome-Wide Association Study
Abstract

Genome-wide association studies (GWASs) of follicular lymphoma (FL) have previously identified human leukocyte antigen (HLA) gene variants. To identify additional FL susceptibility loci, we conducted a large-scale two-stage GWAS in 4,523 case subjects and 13,344 control subjects of European ancestry. Five non-HLA loci were associated with FL risk: 11q23.3 (rs4938573, p = 5.79 × 10(-20)) near CXCR5; 11q24.3 (rs4937362, p = 6.76 × 10(-11)) near ETS1; 3q28 (rs6444305, p = 1.10 × 10(-10)) in LPP; 18q21.33 (rs17749561, p = 8.28 × 10(-10)) near BCL2; and 8q24.21 (rs13254990, p = 1.06 × 10(-8)) near PVT1. In an analysis of the HLA region, we identified four linked HLA-DRβ1 multiallelic amino acids at positions 11, 13, 28, and 30 that were associated with FL risk (pomnibus = 4.20 × 10(-67) to 2.67 × 10(-70)). Additional independent signals included rs17203612 in HLA class II (odds ratio [OR(per-allele)] = 1.44; p = 4.59 × 10(-16)) and rs3130437 in HLA class I (OR(per-allele) = 1.23; p = 8.23 × 10(-9)). Our findings further expand the number of loci associated with FL and provide evidence that multiple common variants outside the HLA region make a significant contribution to FL risk.

Published
2014

22. Genome-wide association study identifies multiple risk loci for chronic lymphocytic leukemia

Author

Berndt, Sonja I, Skibola, Christine F, Joseph, Vijai, Camp, Nicola J, Nieters, Alexandra, Wang, Zhaoming, Cozen, Wendy, Monnereau, Alain, Wang, Sophia S, Kelly, Rachel S, Lan, Qing, Teras, Lauren R, Chatterjee, Nilanjan, Chung, Charles C, Yeager, Meredith, Brooks-Wilson, Angela R, Hartge, Patricia, Purdue, Mark P, Birmann, Brenda M, Armstrong, Bruce K, Cocco, Pierluigi, Zhang, Yawei, Severi, Gianluca, Zeleniuch-Jacquotte, Anne, Lawrence, Charles, Burdette, Laurie, Yuenger, Jeffrey, Hutchinson, Amy, Jacobs, Kevin B, Call, Timothy G, Shanafelt, Tait D, Novak, Anne J, Kay, Neil E, Liebow, Mark, Wang, Alice H, Smedby, Karin E, Adami, Hans-Olov, Melbye, Mads, Glimelius, Bengt, Chang, Ellen T, Glenn, Martha, Curtin, Karen, Cannon-Albright, Lisa A, Jones, Brandt, Diver, W Ryan, Link, Brian K, Weiner, George J, Conde, Lucia, Bracci, Paige M, Riby, Jacques, Holly, Elizabeth A, Smith, Martyn T, Jackson, Rebecca D, Tinker, Lesley F, Benavente, Yolanda, Becker, Nikolaus, Boffetta, Paolo, Brennan, Paul, Foretova, Lenka, Maynadie, Marc, McKay, James, Staines, Anthony, Rabe, Kari G, Achenbach, Sara J, Vachon, Celine M, Goldin, Lynn R, Strom, Sara S, Lanasa, Mark C, Spector, Logan G, Leis, Jose F, Cunningham, Julie M, Weinberg, J Brice, Morrison, Vicki A, Caporaso, Neil E, Norman, Aaron D, Linet, Martha S, De Roos, Anneclaire J, Morton, Lindsay M, Severson, Richard K, Riboli, Elio, Vineis, Paolo, Kaaks, Rudolph, Trichopoulos, Dimitrios, Masala, Giovanna, Weiderpass, Elisabete, Chirlaque, María-Dolores, Vermeulen, Roel CH, Travis, Ruth C, Giles, Graham G, Albanes, Demetrius, Virtamo, Jarmo, Weinstein, Stephanie, Clavel, Jacqueline, Zheng, Tongzhang, Holford, Theodore R, Offit, Kenneth, Zelenetz, Andrew, Klein, Robert J, Spinelli, John J, and Bertrand, Kimberly A

Subjects
Risk, Leukemia, B-Cell, Single Nucleotide, Biological Sciences, Medical and Health Sciences, Chromosomes, Recombination, Linkage Disequilibrium, Lymphocytic, Genetic, Genetic Loci, Case-Control Studies, Pair 2, Humans, Genetic Predisposition to Disease, Polymorphism, Chronic, Human, Genome-Wide Association Study, Developmental Biology
Abstract

Genome-wide association studies (GWAS) have previously identified 13 loci associated with risk of chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL). To identify additional CLL susceptibility loci, we conducted the largest meta-analysis for CLL thus far, including four GWAS with a total of 3,100 individuals with CLL (cases) and 7,667 controls. In the meta-analysis, we identified ten independent associated SNPs in nine new loci at 10q23.31 (ACTA2 or FAS (ACTA2/FAS), P=1.22×10(-14)), 18q21.33 (BCL2, P=7.76×10(-11)), 11p15.5 (C11orf21, P=2.15×10(-10)), 4q25 (LEF1, P=4.24×10(-10)), 2q33.1 (CASP10 or CASP8 (CASP10/CASP8), P=2.50×10(-9)), 9p21.3 (CDKN2B-AS1, P=1.27×10(-8)), 18q21.32 (PMAIP1, P=2.51×10(-8)), 15q15.1 (BMF, P=2.71×10(-10)) and 2p22.2 (QPCT, P=1.68×10(-8)), as well as an independent signal at an established locus (2q13, ACOXL, P=2.08×10(-18)). We also found evidence for two additional promising loci below genome-wide significance at 8q22.3 (ODF1, P=5.40×10(-8)) and 5p15.33 (TERT, P=1.92×10(-7)). Although further studies are required, the proximity of several of these loci to genes involved in apoptosis suggests a plausible underlying biological mechanism.

Published
2013

23. Genome-wide association study identifies multiple risk loci for chronic lymphocytic leukemia

Author

Berndt, Sonja I, Skibola, Christine F, Joseph, Vijai, Camp, Nicola J, Nieters, Alexandra, Wang, Zhaoming, Cozen, Wendy, Monnereau, Alain, Wang, Sophia S, Kelly, Rachel S, Lan, Qing, Teras, Lauren R, Chatterjee, Nilanjan, Chung, Charles C, Yeager, Meredith, Brooks-Wilson, Angela R, Hartge, Patricia, Purdue, Mark P, Birmann, Brenda M, Armstrong, Bruce K, Cocco, Pierluigi, Zhang, Yawei, Severi, Gianluca, Zeleniuch-Jacquotte, Anne, Lawrence, Charles, Burdette, Laurie, Yuenger, Jeffrey, Hutchinson, Amy, Jacobs, Kevin B, Call, Timothy G, Shanafelt, Tait D, Novak, Anne J, Kay, Neil E, Liebow, Mark, Wang, Alice H, Smedby, Karin E, Adami, Hans-Olov, Melbye, Mads, Glimelius, Bengt, Chang, Ellen T, Glenn, Martha, Curtin, Karen, Cannon-Albright, Lisa A, Jones, Brandt, Diver, W Ryan, Link, Brian K, Weiner, George J, Conde, Lucia, Bracci, Paige M, Riby, Jacques, Holly, Elizabeth A, Smith, Martyn T, Jackson, Rebecca D, Tinker, Lesley F, Benavente, Yolanda, Becker, Nikolaus, Boffetta, Paolo, Brennan, Paul, Foretova, Lenka, Maynadie, Marc, McKay, James, Staines, Anthony, Rabe, Kari G, Achenbach, Sara J, Vachon, Celine M, Goldin, Lynn R, Strom, Sara S, Lanasa, Mark C, Spector, Logan G, Leis, Jose F, Cunningham, Julie M, Weinberg, J Brice, Morrison, Vicki A, Caporaso, Neil E, Norman, Aaron D, Linet, Martha S, De Roos, Anneclaire J, Morton, Lindsay M, Severson, Richard K, Riboli, Elio, Vineis, Paolo, Kaaks, Rudolph, Trichopoulos, Dimitrios, Masala, Giovanna, Weiderpass, Elisabete, Chirlaque, María-Dolores, Vermeulen, Roel CH, Travis, Ruth C, Giles, Graham G, Albanes, Demetrius, Virtamo, Jarmo, Weinstein, Stephanie, Clavel, Jacqueline, Zheng, Tongzhang, Holford, Theodore R, Offit, Kenneth, Zelenetz, Andrew, Klein, Robert J, Spinelli, John J, and Bertrand, Kimberly A

Subjects
Risk, Leukemia, B-Cell, Single Nucleotide, Biological Sciences, Medical and Health Sciences, Chromosomes, Recombination, Linkage Disequilibrium, Lymphocytic, Genetic, Genetic Loci, Case-Control Studies, Pair 2, Humans, Genetic Predisposition to Disease, Polymorphism, Chronic, Human, Genome-Wide Association Study, Cancer, Developmental Biology
Abstract

Genome-wide association studies (GWAS) have previously identified 13 loci associated with risk of chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL). To identify additional CLL susceptibility loci, we conducted the largest meta-analysis for CLL thus far, including four GWAS with a total of 3,100 individuals with CLL (cases) and 7,667 controls. In the meta-analysis, we identified ten independent associated SNPs in nine new loci at 10q23.31 (ACTA2 or FAS (ACTA2/FAS), P=1.22×10(-14)), 18q21.33 (BCL2, P=7.76×10(-11)), 11p15.5 (C11orf21, P=2.15×10(-10)), 4q25 (LEF1, P=4.24×10(-10)), 2q33.1 (CASP10 or CASP8 (CASP10/CASP8), P=2.50×10(-9)), 9p21.3 (CDKN2B-AS1, P=1.27×10(-8)), 18q21.32 (PMAIP1, P=2.51×10(-8)), 15q15.1 (BMF, P=2.71×10(-10)) and 2p22.2 (QPCT, P=1.68×10(-8)), as well as an independent signal at an established locus (2q13, ACOXL, P=2.08×10(-18)). We also found evidence for two additional promising loci below genome-wide significance at 8q22.3 (ODF1, P=5.40×10(-8)) and 5p15.33 (TERT, P=1.92×10(-7)). Although further studies are required, the proximity of several of these loci to genes involved in apoptosis suggests a plausible underlying biological mechanism.

Published
2013

25. Additional file 1: Table S1. of Residential particulate matter and distance to roadways in relation to mammographic density: results from the Nursesâ Health Studies

Author

DuPre, Natalie, Hart, Jaime, Bertrand, Kimberly, Kraft, Peter, Laden, Francine, and Rulla Tamimi

Subjects
11. Sustainability
Abstract

Presenting adjusted estimates (95% CI) of the difference in square-root-transformed mammographic dense area and nondense area for a 10-Îźg/m3 increase in PM among premenopausal and postmenopausal women residing across the United States and within regions, and Table S2. presenting adjusted estimates (95% CI) of the difference in untransformed mammographic density measures for a 10-Îźg/m3 increase in PM using bootstrapped robust standard errors (DOCX 33 kb)

26. Additional file 2: Figure S1. of Mammographic texture and risk of breast cancer by tumor type and estrogen receptor status

Author

Malkov, Serghei, Shepherd, John, Scott, Christopher, Rulla Tamimi, Ma, Lin, Bertrand, Kimberly, Couch, Fergus, Jensen, Matthew, Mahmoudzadeh, Amir, Fan, Bo, Norman, Aaron, Brandt, Kathleen, V. Pankratz, Celine Vachon, and Kerlikowske, Karla

Subjects
nutritional and metabolic diseases, 10. No inequality
Abstract

Dendrogram of cluster analysis of the top 15 features with PD, age and BMI. Similar features cluster together. Percent density groups closely with BMI and age. The figure is restricted to the cases. (PDF 76 kb)

27. Additional file 1: of Environmental radon exposure and breast cancer risk in the Nursesâ Health Study II

Author

VoPham, Trang, DuPrĂŠ, Natalie, Rulla Tamimi, James, Peter, Bertrand, Kimberly, Vieira, Veronica, Laden, Francine, and Hart, Jaime

Subjects
social sciences, respiratory tract diseases, 3. Good health
Abstract

Supplemental tables for states in the U.S. Census Bureau regions, model building, associations between radon and breast cancer risk among premenopausal women, associations between radon and breast cancer risk among postmenopausal women, using the EPA radon action level, and stratified analyses by residential mobility. (DOCX 69Â kb)

34. Polyclonal human antibodies against glycans bearing red meat-derived non-human sialic acid N-glycolylneuraminic acid are stable, reproducible, complex and vary between individuals: Total antibody levels are associated with colorectal cancer risk

Author

Samraj, Annie N, Bertrand, Kimberly A, Luben, Robert, Khedri, Zahra, Yu, Hai, Nguyen, Dzung, Gregg, Christopher J, Diaz, Sandra L, Sawyer, Sherilyn, Chen, Xi, Eliassen, Heather, Padler-Karavani, Vered, Wu, Kana, Khaw, Kay-Tee, Willett, Walter, and Varki, Ajit

Subjects
Adult, Middle Aged, Atherosclerosis, Autoantigens, Antibodies, N-Acetylneuraminic Acid, 3. Good health, Epitopes, Red Meat, Diabetes Mellitus, Type 2, Polysaccharides, Risk Factors, Humans, Female, Neuraminic Acids, Colorectal Neoplasms, Aged
Abstract

BACKGROUND: N-glycolylneuraminic acid (Neu5Gc) is a non-human red-meat-derived sialic acid immunogenic to humans. Neu5Gc can be metabolically incorporated into glycan chains on human endothelial and epithelial surfaces. This represents the first example of a "xeno-autoantigen", against which circulating human "xeno-autoantibodies" can react. The resulting inflammation ("xenosialitis") has been demonstrated in human-like Neu5Gc-deficient mice and contributed to carcinoma progression via antibody-mediated inflammation. Anti-Neu5Gc antibodies have potential as biomarkers for diseases associated with red meat consumption such as carcinomas, atherosclerosis, and type 2 diabetes. METHODS: ELISA assays measured antibodies against Neu5Gc or Neu5Gc-glycans in plasma or serum samples from the Nurses' Health Studies, the Health Professionals Follow-up Study, and the European Prospective Investigation into Cancer and Nutrition, including inter-assay reproducibility, stability with delayed sample processing, and within-person reproducibility over 1-3 years in archived samples. We also assessed associations between antibody levels and coronary artery disease risk (CAD) or red meat intake. A glycan microarray was used to detected antibodies against multiple Neu5Gc-glycan epitopes. A nested case-control study design assessed the association between total anti-Neu5Gc antibodies detected in the glycan array assay and the risk of colorectal cancer (CRC). RESULTS: ELISA assays showed a wide range of anti-Neu5Gc responses and good inter-assay reproducibility, stability with delayed sample processing, and within-person reproducibility over time, but these antibody levels did not correlate with CAD risk or red meat intake. Antibodies against Neu5Gc alone or against individual Neu5Gc-bearing epitopes were also not associated with colorectal cancer (CRC) risk. However, a sialoglycan microarray study demonstrated positive association with CRC risk when the total antibody responses against all Neu5Gc-glycans were combined. Individuals in the top quartile of total anti-Neu5Gc IgG antibody concentrations had nearly three times the risk compared to those in the bottom quartile (Multivariate Odds Ratio comparing top to bottom quartile: 2.98, 95% CI: 0.80, 11.1; P for trend = 0.02). CONCLUSIONS: Further work harnessing the utility of these anti-Neu5Gc antibodies as biomarkers in red meat-associated diseases must consider diversity in individual antibody profiles against different Neu5Gc-bearing glycans. Traditional ELISA assays for antibodies directed against Neu5Gc alone, or against specific Neu5Gc-glycans may not be adequate to define risk associations. Our finding of a positive association of total anti-Neu5Gc antibodies with CRC risk also warrants confirmation in larger prospective studies.

35. Additional file 1: of Body mass index, mammographic density, and breast cancer risk by estrogen receptor subtype

Author

Yiwey Shieh, Scott, Christopher, Jensen, Matthew, Norman, Aaron, Bertrand, Kimberly, V. Pankratz, Brandt, Kathleen, Visscher, Daniel, Shepherd, John, Rulla Tamimi, Celine Vachon, and Kerlikowske, Karla

Subjects
2. Zero hunger, 10. No inequality, 3. Good health
Abstract

Figure S1. Flow diagram of subjects included in pooled analysis. Table S1. Baseline characteristics of 6543 women, by study. Table S2. Associations of percent density with ER-positive and ER-negative invasive breast cancer, by menopausal status for 1823 cases and 4720 controls. Table S3. Associations of percent density with ER-positive and ER-negative breast cancer, by BMI (normal/underweight, overweight, obese) and menopausal status for 1823 cases and 4720 controls. Table S4. Associations of percent density with ER-positive and ER-negative breast cancer, by BMI and menopausal status for 1330 Caucasian cases and 3365 Caucasian controls. Table S5. Associations of percent density with ER-positive and ER-negative breast cancer, by BMI and menopausal status, and adjusted for year of index mammogram, for 1823 cases and 4720 controls. (DOCX 2426 kb)

38. Additional file 2: of Exposure to hazardous air pollutants and risk of incident breast cancer in the nursesâ health study II

Author

Hart, Jaime, Bertrand, Kimberly, DuPre, Natalie, James, Peter, VerĂłnica Vieira, VoPham, Trang, Mittleman, Maggie, Rulla Tamimi, and Laden, Francine

Subjects
3. Good health
Abstract

Multivariable adjusted associations of increasing quartiles of each mammary carcinogen HAP exposure on risk of incident invasive overall, estrogen-receptor positive (ER+) or estrogen-receptor negative (ER-) breast cancer 1989â 2011 among 109,239 members of the Nursesâ Health Study II cohort (DOCX 51 kb)

41. Additional file 1: Table S1. of Residential particulate matter and distance to roadways in relation to mammographic density: results from the Nursesâ Health Studies

Author

DuPre, Natalie, Hart, Jaime, Bertrand, Kimberly, Kraft, Peter, Laden, Francine, and Rulla Tamimi

Subjects
11. Sustainability
Abstract

Presenting adjusted estimates (95% CI) of the difference in square-root-transformed mammographic dense area and nondense area for a 10-Îźg/m3 increase in PM among premenopausal and postmenopausal women residing across the United States and within regions, and Table S2. presenting adjusted estimates (95% CI) of the difference in untransformed mammographic density measures for a 10-Îźg/m3 increase in PM using bootstrapped robust standard errors (DOCX 33 kb)

42. Additional file 1: of Body mass index, mammographic density, and breast cancer risk by estrogen receptor subtype

Author

Yiwey Shieh, Scott, Christopher, Jensen, Matthew, Norman, Aaron, Bertrand, Kimberly, V. Pankratz, Brandt, Kathleen, Visscher, Daniel, Shepherd, John, Rulla Tamimi, Celine Vachon, and Kerlikowske, Karla

Subjects
2. Zero hunger, 10. No inequality, 3. Good health
Abstract

Figure S1. Flow diagram of subjects included in pooled analysis. Table S1. Baseline characteristics of 6543 women, by study. Table S2. Associations of percent density with ER-positive and ER-negative invasive breast cancer, by menopausal status for 1823 cases and 4720 controls. Table S3. Associations of percent density with ER-positive and ER-negative breast cancer, by BMI (normal/underweight, overweight, obese) and menopausal status for 1823 cases and 4720 controls. Table S4. Associations of percent density with ER-positive and ER-negative breast cancer, by BMI and menopausal status for 1330 Caucasian cases and 3365 Caucasian controls. Table S5. Associations of percent density with ER-positive and ER-negative breast cancer, by BMI and menopausal status, and adjusted for year of index mammogram, for 1823 cases and 4720 controls. (DOCX 2426 kb)

44. Additional file 2: of Exposure to hazardous air pollutants and risk of incident breast cancer in the Nurses’ Health Study II

Author

Hart, Jaime, Bertrand, Kimberly, DuPre, Natalie, James, Peter, Vieira, Verónica, VoPham, Trang, Mittleman, Maggie, Rulla Tamimi, and Laden, Francine

Subjects
3. Good health
Abstract

Multivariable adjusted associations of increasing quartiles of each mammary carcinogen HAP exposure on risk of incident invasive overall, estrogen-receptor positive (ER+) or estrogen-receptor negative (ER-) breast cancer 1989–2011 among 109,239 members of the Nurses’ Health Study II cohort (DOCX 51 kb)

45. Additional file 1: of Environmental radon exposure and breast cancer risk in the Nursesâ Health Study II

Author

VoPham, Trang, DuPrĂŠ, Natalie, Rulla Tamimi, James, Peter, Bertrand, Kimberly, Vieira, Veronica, Laden, Francine, and Hart, Jaime

Subjects
social sciences, respiratory tract diseases, 3. Good health
Abstract

Supplemental tables for states in the U.S. Census Bureau regions, model building, associations between radon and breast cancer risk among premenopausal women, associations between radon and breast cancer risk among postmenopausal women, using the EPA radon action level, and stratified analyses by residential mobility. (DOCX 69Â kb)

Catalog

Books, media, physical & digital resources
See catalog results