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2. A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Author

Middha, Pooja, Wang, Xiaoliang, Behrens, Sabine, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Michailidou, Kyriaki, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Augustinsson, Annelie, Baert, Thaïs, Freeman, Laura E Beane, Becher, Heiko, Beckmann, Matthias W, Benitez, Javier, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Brooks-Wilson, Angela, Campa, Daniele, Canzian, Federico, Carracedo, Angel, Castelao, Jose E, Chanock, Stephen J, Chenevix-Trench, Georgia, Cordina-Duverger, Emilie, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dossus, Laure, Dugué, Pierre-Antoine, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine D, Fletcher, Olivia, Flyger, Henrik, Gabrielson, Marike, Gago-Dominguez, Manuela, Giles, Graham G, González-Neira, Anna, Grassmann, Felix, Grundy, Anne, Guénel, Pascal, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hankinson, Susan E, Harkness, Elaine F, Holleczek, Bernd, Hoppe, Reiner, Hopper, John L, Houlston, Richard S, Howell, Anthony, Hunter, David J, Ingvar, Christian, Isaksson, Karolin, Jernström, Helena, John, Esther M, Jones, Michael E, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Kurian, Allison W, Lacey, James V, Lambrechts, Diether, Larson, Nicole L, Larsson, Susanna, Le Marchand, Loic, Lejbkowicz, Flavio, Li, Shuai, Linet, Martha, Lissowska, Jolanta, Martinez, Maria Elena, Maurer, Tabea, Mulligan, Anna Marie, Mulot, Claire, Murphy, Rachel A, Newman, William G, Nielsen, Sune F, Nordestgaard, Børge G, Norman, Aaron, O’Brien, Katie M, Olson, Janet E, Patel, Alpa V, Prentice, Ross, Rees-Punia, Erika, Rennert, Gad, Rhenius, Valerie, Ruddy, Kathryn J, and Sandler, Dale P

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Cancer Genomics, Human Genome, Estrogen, Cancer, Women's Health, Genetics, Prevention, Aging, Breast Cancer, 2.1 Biological and endogenous factors, Adult, Female, Humans, Gene-Environment Interaction, Genetic Predisposition to Disease, Breast Neoplasms, Bayes Theorem, Genome-Wide Association Study, Risk Factors, Polymorphism, Single Nucleotide, Case-Control Studies, Breast cancer, Gene-environment interactions, Genetic epidemiology, European ancestry, CTS Consortium, ABCTB Investigators, kConFab Investigators, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundGenome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.MethodsAnalyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.ResultsAssuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability

Published
2023

3. Does a Multiple Myeloma Polygenic Risk Score Predict Overall Survival of Patients with Myeloma?

Author

Macauda, Angelica, Clay-Gilmour, Alyssa, Hielscher, Thomas, Hildebrandt, Michelle, Kruszewski, Marcin, Orlowski, Robert, Kumar, Shaji, Ziv, Elad, Orciuolo, Enrico, Brown, Elizabeth, Försti, Asta, Waller, Rosalie, Machiela, Mitchell, Chanock, Stephen, Camp, Nicola, Rymko, Marcin, Raźny, Małgorzata, Cozen, Wendy, Várkonyi, Judit, Piredda, Chiara, Pelosini, Matteo, Belachew, Alem, Subocz, Edyta, Hemminki, Kari, Rybicka-Ramos, Malwina, Giles, Graham, Milne, Roger, Hofmann, Jonathan, Zaucha, Jan, Vangsted, Annette, Goldschmidt, Hartmut, Rajkumar, S, Tomczak, Waldemar, Sainz, Juan, Butrym, Aleksandra, Watek, Marzena, Iskierka-Jazdzewska, Elżbieta, Buda, Gabriele, Robinson, Dennis, Jurczyszyn, Artur, Dudziński, Marek, Martinez-Lopez, Joaquin, Sinnwell, Jason, Slager, Susan, Jamroziak, Krzysztof, Reis, Rui, Weinhold, Niels, Bhatti, Parveen, Carvajal-Carmona, Luis, Zawirska, Daria, Norman, Aaron, Mazur, Grzegorz, Berndt, Sonja, Campa, Daniele, Vachon, Celine, and Canzian, Federico

Subjects
Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Multiple Myeloma, Polymorphism, Single Nucleotide, Risk Factors
Abstract

BACKGROUND: Genome-wide association studies (GWAS) of multiple myeloma in populations of European ancestry (EA) identified and confirmed 24 susceptibility loci. For other cancers (e.g., colorectum and melanoma), risk loci have also been associated with patient survival. METHODS: We explored the possible association of all the known risk variants and their polygenic risk score (PRS) with multiple myeloma overall survival (OS) in multiple populations of EA [the International Multiple Myeloma rESEarch (IMMEnSE) consortium, the International Lymphoma Epidemiology consortium, CoMMpass, and the German GWAS] for a total of 3,748 multiple myeloma cases. Cox proportional hazards regression was used to assess the association between each risk SNP with OS under the allelic and codominant models of inheritance. All analyses were adjusted for age, sex, country of origin (for IMMEnSE) or principal components (for the others) and disease stage (ISS). SNP associations were meta-analyzed. RESULTS: SNP associations were meta-analyzed. From the meta-analysis, two multiple myeloma risk SNPs were associated with OS (P < 0.05), specifically POT1-AS1-rs2170352 [HR = 1.37; 95% confidence interval (CI) = 1.09-1.73; P = 0.007] and TNFRSF13B-rs4273077 (HR = 1.19; 95% CI = 1.01-1.41; P = 0.04). The association between the combined 24 SNP MM-PRS and OS, however, was not significant. CONCLUSIONS: Overall, our results did not support an association between the majority of multiple myeloma risk SNPs and OS. IMPACT: This is the first study to investigate the association between multiple myeloma PRS and OS in multiple myeloma.

Published
2022

4. Identification of novel genetic loci for risk of multiple myeloma by functional annotation

Author

Macauda, Angelica, Briem, Klara, Clay-Gilmour, Alyssa, Cozen, Wendy, Försti, Asta, Giaccherini, Matteo, Corradi, Chiara, Sainz, Juan, Niazi, Yasmeen, ter Horst, Rob, Li, Yang, Netea, Mihai G., Vogel, Ulla, Hemminki, Kari, Slager, Susan L., Varkonyi, Judit, Andersen, Vibeke, Iskierka-Jazdzewska, Elzbieta, Mártinez-Lopez, Joaquin, Zaucha, Jan, Camp, Nicola J., Rajkumar, S. Vincent, Druzd-Sitek, Agnieszka, Bhatti, Parveen, Chanock, Stephen J., Kumar, Shaji K., Subocz, Edyta, Mazur, Grzegorz, Landi, Stefano, Machiela, Mitchell J., Jerez, Andrés, Norman, Aaron D., Hildebrandt, Michelle A. T., Kadar, Katalin, Berndt, Sonja I., Ziv, Elad, Buda, Gabriele, Nagler, Arnon, Dumontet, Charles, Raźny, Malgorzata, Watek, Marzena, Butrym, Aleksandra, Grzasko, Norbert, Dudzinski, Marek, Rybicka-Ramos, Malwina, Matera, Eva-Laure, García-Sanz, Ramón, Goldschmidt, Hartmut, Jamroziak, Krzysztof, Jurczyszyn, Artur, Clavero, Esther, Giles, Graham G., Pelosini, Matteo, Zawirska, Daria, Kruszewski, Marcin, Marques, Herlander, Haastrup, Eva, Sánchez-Maldonado, José Manuel, Bertsch, Uta, Rymko, Marcin, Raab, Marc-Steffen, Brown, Elizabeth E., Hofmann, Jonathan N., Vachon, Celine, Campa, Daniele, and Canzian, Federico

Published
2023
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5. Relationship among three common hematological premalignant conditions

Author

Boddicker, Nicholas J., Parikh, Sameer A., Norman, Aaron D., Rabe, Kari G., Griffin, Rosalie, Call, Timothy G., Robinson, Dennis P., Olson, Janet E., Dispenzieri, Angela, Rajkumar, Vincent, Kumar, Shaji, Kay, Neil E., Hanson, Curtis A., Cerhan, James R., Murray, David, Braggio, Esteban, Shanafelt, Tait D., Vachon, Celine M., and Slager, Susan L.

Published
2023
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6. Tumor mutational load is prognostic for progression to therapy among high-count monoclonal B-cell lymphocytosis

Author

Kleinstern, Geffen, Boddicker, Nicholas J., O’Brien, Daniel R., Allmer, Cristine, Rabe, Kari G., Norman, Aaron D., Griffin, Rosalie, Yan, Huihuang, Ma, Tao, Call, Timothy G., Bruins, Laura, Brown, Sochilt, Bonolo de Campos, Cecilia, Hanson, Curtis A., Leis, Jose F., Ding, Wei, Vachon, Celine M., Kay, Neil E., Oakes, Christopher C., Parker, Alexander S., Brander, Danielle M., Weinberg, J. Brice, Furman, Richard R., Shanafelt, Tait D., Cerhan, James R., Parikh, Sameer A., Braggio, Esteban, and Slager, Susan L.

Published
2024
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8. Polygenic risk score and risk of monoclonal B-cell lymphocytosis in caucasians and risk of chronic lymphocytic leukemia (CLL) in African Americans

Author

Kleinstern, Geffen, Weinberg, J Brice, Parikh, Sameer A, Braggio, Esteban, Achenbach, Sara J, Robinson, Dennis P, Norman, Aaron D, Rabe, Kari G, Boddicker, Nicholas J, Vachon, Celine M, Lesnick, Connie E, Call, Timothy G, Brander, Danielle M, Rassenti, Laura Z, Kipps, Thomas J, Olson, Janet E, Cerhan, James R, Kay, Neil E, Furman, Richard R, Hanson, Curtis A, Shanafelt, Tait D, and Slager, Susan L

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Oncology and Carcinogenesis, Hematology, Lymphoma, Cancer, Prevention, Clinical Research, Rare Diseases, Adult, Black or African American, Aged, Aged, 80 and over, B-Lymphocytes, Biomarkers, Tumor, Case-Control Studies, Clone Cells, Female, Follow-Up Studies, Humans, Immunoglobulins, Immunophenotyping, Leukemia, Lymphocytic, Chronic, B-Cell, Lymphocytosis, Male, Middle Aged, Prognosis, Risk Factors, United States, White People, Immunology, Cardiovascular medicine and haematology, Clinical sciences, Oncology and carcinogenesis
Abstract

Monoclonal B-cell lymphocytosis (MBL) is a precursor to CLL. Other than age, sex, and CLL family-history, little is known about factors associated with MBL risk. A polygenic-risk-score (PRS) of 41 CLL-susceptibility variants has been found to be associated with CLL risk among individuals of European-ancestry(EA). Here, we evaluate these variants, the PRS, and environmental factors for MBL risk. We also evaluate these variants and the CLL-PRS among African-American (AA) and EA-CLL cases and controls. Our study included 560 EA MBLs, 869 CLLs (696 EA/173 AA), and 2866 controls (2631 EA/235 AA). We used logistic regression, adjusting for age and sex, to estimate odds ratios (OR) and 95% confidence intervals within each race. We found significant associations with MBL risk among 21 of 41 variants and with the CLL-PRS (OR = 1.86, P = 1.9 × 10-29, c-statistic = 0.72). Little evidence of any association between MBL risk and environmental factors was observed. We observed significant associations of the CLL-PRS with EA-CLL risk (OR = 2.53, P = 4.0 × 10-63, c-statistic = 0.77) and AA-CLL risk (OR = 1.76, P = 5.1 × 10-5, c-statistic = 0.62). Inherited genetic factors and not environmental are associated with MBL risk. In particular, the CLL-PRS is a strong predictor for both risk of MBL and EA-CLL, but less so for AA-CLL supporting the need for further work in this population.

Published
2022

10. Antimullerian Hormone as a Serum Biomarker for Risk of Chemotherapy-Induced Amenorrhea.

Author

Ruddy, Kathryn J, Schaid, Daniel J, Batzler, Anthony, Cecchini, Reena S, Partridge, Ann H, Norman, Aaron, Fehrenbacher, Louis, Stewart, Elizabeth A, Trabuco, Emanuel, Ginsburg, Elizabeth, Couch, Fergus J, Fasching, Peter A, Vachon, Celine, and Ganz, Patricia A

Subjects
Aging, Cancer, Clinical Research, Adult, Amenorrhea, Anti-Mullerian Hormone, Antineoplastic Agents, Biomarkers, Breast Neoplasms, Chemotherapy, Adjuvant, Female, Humans, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

Antimullerian hormone (AMH) is a promising biomarker for ovarian reserve. In this study, we assessed AMH before and 1 year after initiation of adjuvant chemotherapy on National Surgical Adjuvant Breast and Bowel Project (NSABP)/NRG Oncology B-47 in female participants aged 42 years and younger (median age = 39 years). At baseline, median AMH was 1.2 ng/mL; 13 (4.7%) values were less than 0.1 ng/mL (the threshold for detectable levels, in the perimenopause and menopause range), and 57 values (20.6%) were less than 0.5 ng/mL. At 1 year, 215 (77.6%) were less than 0.1 ng/mL, and 264 (95.3%) were less than 0.5 ng/mL. Postchemotherapy menses were reported by 46.2% of participants. Multivariable logistic regression found that the odds of having postchemotherapy menses increased with younger age, higher body mass index, and higher prechemotherapy AMH, but not by trastuzumab administration or by the choice of chemotherapy (doxorubicin-cyclophosphamide followed by paclitaxel vs docetaxel-cyclophosphamide). We conclude that higher prechemotherapy AMH predicts a lower risk of chemotherapy-induced amenorrhea and that AMH 1 year after chemotherapy initiation is not informative in this setting because it is likely to be very low.

Published
2021

11. Mammographic Variation Measures, Breast Density, and Breast Cancer Risk.

Author

Heine, John, Fowler, Erin, Scott, Christopher G, Jensen, Matthew R, Shepherd, John, Hruska, Carrie B, Winham, Stacey J, Brandt, Kathleen R, Wu, Fang F, Norman, Aaron D, Pankratz, Vernon S, Miglioretti, Diana L, Kerlikowske, Karla, and Vachon, Celine M

Subjects
Biomedical Imaging, Breast Cancer, Cancer, Aging, Clinical Research, Prevention, Adult, Breast, Breast Density, Breast Neoplasms, Case-Control Studies, Female, Humans, Mammography, Reproducibility of Results, breast cancer, risk prediction, variation measures, volumetric breast density, Clinical Sciences, Nuclear Medicine & Medical Imaging
Abstract

OBJECTIVE. Our previous work showed that variation measures, which represent breast architecture derived from mammograms, were significantly associated with breast cancer. For replication purposes, we examined the association of three variation measures (variation [V], which is measured in the image domain, and P1 and p1 [a normalized version of P1], which are derived from restricted regions in the Fourier domain) with breast cancer risk in an independent population. We also compared these measures to volumetric density measures (volumetric percent density [VPD] and dense volume [DV]) from a commercial product. MATERIALS AND METHODS. We examined 514 patients with breast cancer and 1377 control patients from a screening practice who were matched for age, date of examination, mammography unit, facility, and state of residence. Spearman rank-order correlation was used to evaluate the monotonic association between measures. Breast cancer associations were estimated using conditional logistic regression, after adjustment for age and body mass index. Odds ratios were calculated per SD increment in mammographic measure. RESULTS. These variation measures were strongly correlated with VPD (correlation, 0.68-0.80) but not with DV (correlation, 0.31-0.48). Similar to previous findings, all variation measures were significantly associated with breast cancer (odds ratio per SD: 1.30 [95% CI, 1.16-1.46] for V, 1.55 [95% CI, 1.35-1.77] for P1, and 1.51 [95% CI, 1.33-1.72] for p1). Associations of volumetric density measures with breast cancer were similar (odds ratio per SD: 1.54 [95% CI, 1.33-1.78] for VPD and 1.34 [95% CI, 1.20-1.50] for DV). When DV was included with each variation measure in the same model, all measures retained significance. CONCLUSION. Variation measures were significantly associated with breast cancer risk (comparable to the volumetric density measures) but were independent of the DV.

Published
2021

12. Association of Daily Alcohol Intake, Volumetric Breast Density, and Breast Cancer Risk

Author

Rustagi, Alison S, Scott, Christopher G, Winham, Stacey J, Brandt, Kathleen R, Norman, Aaron D, Jensen, Matthew R, Shepherd, John A, Hruska, Carrie, Heine, John J, Pankratz, Vernon S, Kerlikowske, Karla, and Vachon, Celine M

Subjects
Substance Misuse, Alcoholism, Alcohol Use and Health, Cancer, Clinical Research, Prevention, Breast Cancer, Good Health and Well Being, Age Factors, Alcohol Drinking, Body Mass Index, Breast Density, Breast Neoplasms, Case-Control Studies, Female, Humans, Mammography, Menopause, Middle Aged, Odds Ratio, San Francisco
Abstract

High alcohol intake and breast density increase breast cancer (BC) risk, but their interrelationship is unknown. We examined whether volumetric density modifies and/or mediates the alcohol-BC association. BC cases (n = 2233) diagnosed from 2006 to 2013 in the San Francisco Bay area had screening mammograms 6 or more months before diagnosis; controls (n = 4562) were matched on age, mammogram date, race or ethnicity, facility, and mammography machine. Logistic regression was used to estimate alcohol-BC associations adjusted for age, body mass index, and menopause; interaction terms assessed modification. Percent mediation was quantified as the ratio of log (odds ratios [ORs]) from models with and without density measures. Alcohol consumption was associated with increased BC risk (2-sided Ptrend = .004), as were volumetric percent density (OR = 1.45 per SD, 95% confidence interval [CI] = 1.36 to 1.56) and dense volume (OR = 1.30, 95% CI = 1.24 to 1.37). Breast density did not modify the alcohol-BC association (2-sided P > .10 for all). Dense volume mediated 25.0% (95% CI = 5.5% to 44.4%) of the alcohol-BC association (2-sided P = .01), suggesting alcohol may partially increase BC risk by increasing fibroglandular tissue.

Published
2021

13. Combined Associations of a Polygenic Risk Score and Classical Risk Factors With Breast Cancer Risk.

Author

Kapoor, Pooja Middha, Mavaddat, Nasim, Choudhury, Parichoy Pal, Wilcox, Amber N, Lindström, Sara, Behrens, Sabine, Michailidou, Kyriaki, Dennis, Joe, Bolla, Manjeet K, Wang, Qin, Jung, Audrey, Abu-Ful, Zomoroda, Ahearn, Thomas, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Freeman, Laura E Beane, Becher, Heiko, Beckmann, Matthias W, Beeghly-Fadiel, Alicia, Benitez, Javier, Bernstein, Leslie, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Brüning, Thomas, Cai, Qiuyin, Campa, Daniele, Canzian, Federico, Carracedo, Angel, Carter, Brian D, Castelao, Jose E, Chanock, Stephen J, Chatterjee, Nilanjan, Chenevix-Trench, Georgia, Clarke, Christine L, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dai, James Y, Earp, H Shelton, Ekici, Arif B, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, Gao, Chi, Gapstur, Susan M, Gaudet, Mia M, Giles, Graham G, González-Neira, Anna, Guénel, Pascal, Haeberle, Lothar, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hatse, Sigrid, Heyworth, Jane, Holleczek, Bernd, Hoover, Robert N, Hopper, John L, Howell, Anthony, Hunter, David J, ABCTB Investigators, kConFab/AOCS Investigators, John, Esther M, Jones, Michael E, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Kurian, Allison W, Lambrechts, Diether, Le Marchand, Loic, Lee, Eunjung, Lejbkowicz, Flavio, Linet, Martha, Lissowska, Jolanta, Llaneza, Ana, MacInnis, Robert J, Martinez, Maria Elena, Maurer, Tabea, McLean, Catriona, Neuhausen, Susan L, Newman, William G, Norman, Aaron, O'Brien, Katie M, Olshan, Andrew F, Olson, Janet E, Olsson, Håkan, and Orr, Nick

Subjects
ABCTB Investigators, kConFab/AOCS Investigators, Oncology & Carcinogenesis, Oncology and Carcinogenesis
Abstract

We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.

Published
2021

14. Association of EDARV370A with breast density and metabolic syndrome in Latinos

Author

Coletta, Dawn K, Hlusko, Leslea J, Scott, G Richard, Garcia, Luis A, Vachon, Celine M, Norman, Aaron D, Funk, Janet L, Shaibi, Gabriel Q, Hernandez, Valentina, De Filippis, Eleanna, and Mandarino, Lawrence J

Subjects
Health Services and Systems, Biomedical and Clinical Sciences, Health Sciences, Clinical Research, Nutrition, Genetics, Diabetes, Breast Cancer, Cancer, Obesity, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Adult, Advisory Committees, Arizona, Biological Specimen Banks, Blood Glucose, Breast Density, Ectodysplasins, Edar Receptor, Female, Gene Frequency, Genetic Association Studies, Genetic Predisposition to Disease, Glycated Hemoglobin, Hispanic or Latino, Humans, Insulin Resistance, Male, Metabolic Syndrome, Middle Aged, Mutation, Registries, General Science & Technology
Abstract

The ectodysplasin receptor (EDAR) is a tumor necrosis factor receptor (TNF) superfamily member. A substitution in an exon of EDAR at position 370 (EDARV370A) creates a gain of function mutant present at high frequencies in Asian and Indigenous American populations but absent in others. Its frequency is intermediate in populations of Mexican ancestry. EDAR regulates the development of ectodermal tissues, including mammary ducts. Obesity and type 2 diabetes mellitus are prevalent in people with Indigenous and Latino ancestry. Latino patients also have altered prevalence and presentation of breast cancer. It is unknown whether EDARV370A might connect these phenomena. The goals of this study were to determine 1) whether EDARV370A is associated with metabolic phenotypes and 2) if there is altered breast anatomy in women carrying EDARV370A. Participants were from two Latino cohorts, the Arizona Insulin Resistance (AIR) registry and Sangre por Salud (SPS) biobank. The frequency of EDARV370A was 47% in the Latino cohorts. In the AIR registry, carriers of EDARV370A (GG homozygous) had significantly (p < 0.05) higher plasma triglycerides, VLDL, ALT, 2-hour post-challenge glucose, and a higher prevalence of prediabetes/diabetes. In a subset of the AIR registry, serum levels of ectodysplasin A2 (EDA-A2) also were associated with HbA1c and prediabetes (p < 0.05). For the SPS biobank, participants that were carriers of EDARV370A had lower breast density and higher HbA1c (both p < 0.05). The significant associations with measures of glycemia remained when the cohorts were combined. We conclude that EDARV370A is associated with characteristics of the metabolic syndrome and breast density in Latinos.

Published
2021

15. Automated volumetric breast density measures: differential change between breasts in women with and without breast cancer

Author

Brandt, Kathleen R, Scott, Christopher G, Miglioretti, Diana L, Jensen, Matthew R, Mahmoudzadeh, Amir P, Hruska, Carrie, Ma, Lin, Wu, Fang Fang, Cummings, Steven R, Norman, Aaron D, Engmann, Natalie J, Shepherd, John A, Winham, Stacey J, Kerlikowske, Karla, and Vachon, Celine M

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Biomedical Imaging, Clinical Research, Prevention, Breast Cancer, Cancer, Aged, Automation, Breast, Breast Density, Breast Neoplasms, Case-Control Studies, Early Detection of Cancer, Female, Humans, Mammography, Middle Aged, Reproducibility of Results, Sensitivity and Specificity, Tumor Burden, Volumetric density, Breast density, Breast cancer, Tissue asymmetry, Risk, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundGiven that breast cancer and normal dense fibroglandular tissue have similar radiographic attenuation, we examine whether automated volumetric density measures identify a differential change between breasts in women with cancer and compare to healthy controls.MethodsEligible cases (n = 1160) had unilateral invasive breast cancer and bilateral full-field digital mammograms (FFDMs) at two time points: within 2 months and 1-5 years before diagnosis. Controls (n = 2360) were matched to cases on age and date of FFDMs. Dense volume (DV) and volumetric percent density (VPD) for each breast were assessed using Volpara™. Differences in DV and VPD between mammograms (median 3 years apart) were calculated per breast separately for cases and controls and their difference evaluated by using the Wilcoxon signed-rank test. To simulate clinical practice where cancer laterality is unknown, we examined whether the absolute difference between breasts can discriminate cases from controls using area under the ROC curve (AUC) analysis, adjusting for age, BMI, and time.ResultsAmong cases, the VPD and DV between mammograms of the cancerous breast decreased to a lesser degree (- 0.26% and - 2.10 cm3) than the normal breast (- 0.39% and - 2.74 cm3) for a difference of 0.13% (p value

Published
2019

16. The association between genetically elevated polyunsaturated fatty acids and risk of cancer

Author

Tintle, Nathan, Rice, Terri, Cheng, Iona, Jenkins, Mark, Gallinger, Steve, Cornish, Alex J., Sud, Amit, Vijayakrishnan, Jayaram, Wrensch, Margaret, Johansson, Mattias, Norman, Aaron D., Klein, Alison, Clay-Gilmour, Alyssa, Franke, Andre, Ardisson Korat, Andres V., Wheeler, Bill, Nilsson, Björn, Smith, Caren, Heng, Chew-Kiat, Song, Ci, Riadi, David, Claus, Elizabeth B., Ellinghaus, Eva, Ostroumova, Evgenia, Hosnijeh, de Vathaire, Florent, Cugliari, Giovanni, Matullo, Giuseppe, Oi-Lin Ng, Irene, Passow, Jeanette E., Foo, Jia Nee, Han, Jiali, Liu, Jianjun, Barnholtz-Sloan, Jill, Schildkraut, Joellen M., Maris, John, Wiemels, Joseph L., Hemminki, Kari, Yang, Keming, Kiemeney, Lambertus A., Wu, Lang, Amundadottir, Laufey, Stern, Marc-Henri, Boutron, Marie-Christine, Iles, Mark Martin, Purdue, Mark P., Stanulla, Martin, Bondy, Melissa, Gaudet, Mia, Mobuchon, Lenha, Camp, Nicola J., Sham, Pak Chung, Guénel, Pascal, Brennan, Paul, Taylor, Philip R., Ostrom, Quinn, Stolzenberg-Solomon, Rachael, Dorajoo, Rajkumar, Houlston, Richard, Jenkins, Robert B., Diskin, Sharon, Berndt, Sonja I., Tsavachidis, Spiridon, Channock, Stephen J., Harrison, Tabitha, Galesloot, Tessel, Gyllensten, Ulf, Joseph, Vijai, Shi, Y., Yang, Wenjian, Lin, Yi, Van Den Eeden, Stephen K., Haycock, Philip C., Borges, Maria Carolina, Burrows, Kimberley, Lemaitre, Rozenn N., Burgess, Stephen, Khankari, Nikhil K., Tsilidis, Konstantinos K., Gaunt, Tom R., Hemani, Gibran, Zheng, Jie, Truong, Therese, Birmann, Brenda M., OMara, Tracy, Spurdle, Amanda B., Iles, Mark M., Law, Matthew H., Slager, Susan L., Saberi Hosnijeh, Fatemeh, Mariosa, Daniela, Cotterchio, Michelle, Cerhan, James R., Peters, Ulrike, Enroth, Stefan, Gharahkhani, Puya, Le Marchand, Loic, Williams, Ann C., Block, Robert C., Amos, Christopher I., Hung, Rayjean J., Zheng, Wei, Gunter, Marc J., Smith, George Davey, Relton, Caroline, and Martin, Richard M.

Published
2023
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17. Rates of Asymptomatic COVID-19 Infection and Associated Factors in Olmsted County, Minnesota, in the Prevaccination Era

Author

Vachon, Celine M., Norman, Aaron D., Prasad, Kavita, Jensen, Dan, Schaeferle, Gavin M., Vierling, Kristy L., Sherden, Meaghan, Majerus, Michelle R., Bews, Katherine A., Heinzen, Ethan P., Hebl, Amy, Yost, Kathleen J., Kennedy, Richard B., Theel, Elitza S., Ghosh, Aditya, Fries, Meghan, Wi, Chung-Il, Juhn, Young J., Sampathkumar, Priya, Morice, William G., II, Rocca, Walter A., Tande, Aaron J., Cerhan, James R., Limper, Andrew H., Ting, Henry H., Farrugia, Gianrico, Carter, Rickey E., Finney Rutten, Lila J., Jacobson, Robert M., and St. Sauver, Jennifer

Published
2022
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18. Combined effect of volumetric breast density and body mass index on breast cancer risk

Author

Engmann, Natalie J, Scott, Christopher G, Jensen, Matthew R, Winham, Stacey, Miglioretti, Diana L, Ma, Lin, Brandt, Kathleen, Mahmoudzadeh, Amir, Whaley, Dana H, Hruska, Carrie, Wu, Fang, Norman, Aaron D, Hiatt, Robert A, Heine, John, Shepherd, John, Pankratz, V Shane, Vachon, Celine M, and Kerlikowske, Karla

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Biomedical Imaging, Prevention, Clinical Research, Estrogen, Aging, Women's Health, Breast Cancer, Obesity, Cancer, Adult, Aged, Aged, 80 and over, Body Mass Index, Breast Density, Breast Neoplasms, Case-Control Studies, Disease Susceptibility, Early Detection of Cancer, Female, Humans, Mammography, Mass Screening, Menopause, Middle Aged, Public Health Surveillance, Registries, Risk, Breast density, Mammographic density, Breast cancer, Body mass index, Clinical Sciences, Oncology & Carcinogenesis, Clinical sciences, Oncology and carcinogenesis
Abstract

BackgroundBreast density and body mass index (BMI) are used for breast cancer risk stratification. We evaluate whether the positive association between volumetric breast density and breast cancer risk is strengthened with increasing BMI.MethodsThe San Francisco Mammography Registry and Mayo Clinic Rochester identified 781 premenopausal and 1850 postmenopausal women with breast cancer diagnosed between 2007 and 2015 that had a screening digital mammogram at least 6 months prior to diagnosis. Up to three controls (N = 3535) were matched per case on age, race, date, mammography machine, and state. Volumetric percent density (VPD) and dense volume (DV) were measured with Volpara™. Breast cancer risk was assessed with logistic regression stratified by menopause status. Multiplicative interaction tests assessed whether the association of density measures was differential by BMI categories.ResultsThe increased risk of breast cancer associated with VPD was strengthened with higher BMI for both premenopausal (pinteraction = 0.01) and postmenopausal (pinteraction = 0.0003) women. For BMI

Published
2019

19. Longitudinal Changes in Volumetric Breast Density in Healthy Women across the Menopausal Transition

Author

Engmann, Natalie J, Scott, Christopher, Jensen, Matthew R, Winham, Stacey J, Ma, Lin, Brandt, Kathleen R, Mahmoudzadeh, Amir, Whaley, Dana H, Hruska, Carrie B, Wu, Fang-Fang, Norman, Aaron D, Hiatt, Robert A, Heine, John, Shepherd, John, Pankratz, V Shane, Miglioretti, Diana L, Kerlikowske, Karla, and Vachon, Celine M

Subjects
Health Services and Systems, Biomedical and Clinical Sciences, Health Sciences, Oncology and Carcinogenesis, Prevention, Aging, Cancer, Contraception/Reproduction, Breast Cancer, Clinical Research, Estrogen, Biomedical Imaging, Good Health and Well Being, Body Mass Index, Breast, Breast Density, Female, Humans, Longitudinal Studies, Mammography, Middle Aged, Postmenopause, Premenopause, Risk Factors, Women's Health, Women’s Health, Medical and Health Sciences, Epidemiology, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundMammographic breast density declines during menopause. We assessed changes in volumetric breast density across the menopausal transition and factors that influence these changes.MethodsWomen without a history of breast cancer, who had full field digital mammograms during both pre- and postmenopausal periods, at least 2 years apart, were sampled from four facilities within the San Francisco Mammography Registry from 2007 to 2013. Dense breast volume (DV) was assessed using Volpara on mammograms across the time period. Annualized change in DV from pre- to postmenopause was estimated using linear mixed models adjusted for covariates and per-woman random effects. Multiplicative interactions were evaluated between premenopausal risk factors and time to determine whether these covariates modified the annualized changes.ResultsAmong the 2,586 eligible women, 1,802 had one premenopausal and one postmenopausal mammogram, 628 had an additional perimenopausal mammogram, and 156 had two perimenopausal mammograms. Women experienced an annualized decrease in DV [-2.2 cm3 (95% confidence interval, -2.7 to -1.7)] over the menopausal transition. Declines were greater among women with a premenopausal DV above the median (54 cm3) versus below (DV, -3.5 cm3 vs. -1.0 cm3; P < 0.0001). Other breast cancer risk factors, including race, body mass index, family history, alcohol, and postmenopausal hormone therapy, had no effect on change in DV over the menopausal transition.ConclusionsHigh premenopausal DV was a strong predictor of greater reductions in DV across the menopausal transition.ImpactWe found that few factors other than premenopausal density influence changes in DV across the menopausal transition, limiting targeted prevention efforts.

Published
2019

25. Does mammographic density mediate risk factor associations with breast cancer? An analysis by tumor characteristics

Author

Rice, Megan S, Tamimi, Rulla M, Bertrand, Kimberly A, Scott, Christopher G, Jensen, Matthew R, Norman, Aaron D, Visscher, Daniel W, Chen, Yunn-Yi, Brandt, Kathleen R, Couch, Fergus J, Shepherd, John A, Fan, Bo, Wu, Fang-Fang, Ma, Lin, Collins, Laura C, Cummings, Steven R, Kerlikowske, Karla, and Vachon, Celine M

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Cancer, Clinical Research, Breast Cancer, Prevention, Estrogen, Aging, Adult, Aged, Biomarkers, Tumor, Breast, Breast Density, Breast Neoplasms, Female, Humans, Mammography, Middle Aged, Pregnancy, Receptor, ErbB-2, Receptors, Estrogen, Receptors, Progesterone, Risk Factors, Mammographic density, Breast cancer, Receptor, erbB-2, Clinical Sciences, Oncology & Carcinogenesis, Clinical sciences, Oncology and carcinogenesis
Abstract

BackgroundThough mammographic density (MD) has been proposed as an intermediate marker of breast cancer risk, few studies have examined whether the associations between breast cancer risk factors and risk are mediated by MD, particularly by tumor characteristics.MethodsOur study population included 3392 cases (1105 premenopausal) and 8882 (3192 premenopausal) controls from four case-control studies. For established risk factors, we estimated the percent of the total risk factor association with breast cancer that was mediated by percent MD (secondarily, by dense area and non-dense area) for invasive breast cancer as well as for subtypes defined by the estrogen receptor (ER+/ER-), progesterone receptor (PR+/PR-), and HER2 (HER2+/HER2-). Analyses were conducted separately in pre- and postmenopausal women.ResultsPositive associations between prior breast biopsy and risk of invasive breast cancer as well as all subtypes were partially mediated by percent MD in pre- and postmenopausal women (percent mediated = 11-27%, p ≤ 0.02). In postmenopausal women, nulliparity and hormone therapy use were positively associated with invasive, ER+ , PR+ , and HER2- breast cancer; percent MD partially mediated these associations (percent mediated ≥ 31%, p ≤ 0.02). Further, among postmenopausal women, percent MD partially mediated the positive association between later age at first birth and invasive as well as ER+ breast cancer (percent mediated = 16%, p ≤ 0.05).ConclusionPercent MD partially mediated the associations between breast biopsy, nulliparity, age at first birth, and hormone therapy with risk of breast cancer, particularly among postmenopausal women, suggesting that these risk factors at least partially influence breast cancer risk through changes in breast tissue composition.

Published
2018

27. Interaction of mammographic breast density with menopausal status and postmenopausal hormone use in relation to the risk of aggressive breast cancer subtypes.

Author

Chen, Yunn-Yi, Ma, Lin, Beck, Andrew, Cummings, Steven, Kerlikowske, Karla, Vachon, Celine, Yaghjyan, Lusine, Tamimi, Rulla, Bertrand, Kimberly, Scott, Christopher, Jensen, Matthew, Pankratz, V, Brandt, Kathy, Visscher, Daniel, Norman, Aaron, Couch, Fergus, Shepherd, John, and Fan, Bo

Subjects
Breast cancer subtypes, Breast density, Postmenopausal hormone therapy, Tumor aggressiveness, Adult, Breast, Breast Density, Breast Neoplasms, Case-Control Studies, Disease Progression, Estrogen Replacement Therapy, Female, Humans, Menopause, Middle Aged, Odds Ratio, Population Surveillance, Risk
Abstract

PURPOSE: We examined the associations of mammographic breast density with breast cancer risk by tumor aggressiveness and by menopausal status and current postmenopausal hormone therapy. METHODS: This study included 2596 invasive breast cancer cases and 4059 controls selected from participants of four nested case-control studies within four established cohorts: the Mayo Mammography Health Study, the Nurses Health Study, Nurses Health Study II, and San Francisco Mammography Registry. Percent breast density (PD), absolute dense (DA), and non-dense areas (NDA) were assessed from digitized film-screen mammograms using a computer-assisted threshold technique and standardized across studies. We used polytomous logistic regression to quantify the associations of breast density with breast cancer risk by tumor aggressiveness (defined as presence of at least two of the following tumor characteristics: size ≥2 cm, grade 2/3, ER-negative status, or positive nodes), stratified by menopausal status and current hormone therapy. RESULTS: Overall, the positive association of PD and borderline inverse association of NDA with breast cancer risk was stronger in aggressive vs. non-aggressive tumors (≥51 vs. 11-25% OR 2.50, 95% CI 1.94-3.22 vs. OR 2.03, 95% CI 1.70-2.43, p-heterogeneity = 0.03; NDA 4th vs. 2nd quartile OR 0.54, 95% CI 0.41-0.70 vs. OR 0.71, 95% CI 0.59-0.85, p-heterogeneity = 0.07). However, there were no differences in the association of DA with breast cancer by aggressive status. In the stratified analysis, there was also evidence of a stronger association of PD and NDA with aggressive tumors among postmenopausal women and, in particular, current estrogen+progesterone users (≥51 vs. 11-25% OR 3.24, 95% CI 1.75-6.00 vs. OR 1.93, 95% CI 1.25-2.98, p-heterogeneity = 0.01; NDA 4th vs. 2nd quartile OR 0.43, 95% CI 0.21-0.85 vs. OR 0.56, 95% CI 0.35-0.89, p-heterogeneity = 0.01), even though the interaction was not significant. CONCLUSION: Our findings suggest that associations of mammographic density with breast cancer risk differ by tumor aggressiveness. While there was no strong evidence that these associations differed by menopausal status or hormone therapy, they did appear more prominent among current estrogen+progesterone users.

Published
2017

28. Longitudinal Changes in Volumetric Breast Density with Tamoxifen and Aromatase Inhibitors

Author

Engmann, Natalie J, Scott, Christopher G, Jensen, Matthew R, Ma, Lin, Brandt, Kathleen R, Mahmoudzadeh, Amir Pasha, Malkov, Serghei, Whaley, Dana H, Hruska, Carrie B, Wu, Fang Fang, Winham, Stacey J, Miglioretti, Diana L, Norman, Aaron D, Heine, John J, Shepherd, John, Pankratz, V Shane, Vachon, Celine M, and Kerlikowske, Karla

Subjects
Health Services and Systems, Biomedical and Clinical Sciences, Health Sciences, Oncology and Carcinogenesis, Biomedical Imaging, Prevention, Breast Cancer, Aging, Clinical Research, Cancer, Adult, Aromatase Inhibitors, Breast Density, Female, Humans, Middle Aged, Tamoxifen, Medical and Health Sciences, Epidemiology, Biomedical and clinical sciences, Health sciences
Abstract

Background: Reductions in breast density with tamoxifen and aromatase inhibitors may be an intermediate marker of treatment response. We compare changes in volumetric breast density among breast cancer cases using tamoxifen or aromatase inhibitors (AI) to untreated women without breast cancer.Methods: Breast cancer cases with a digital mammogram prior to diagnosis and after initiation of tamoxifen (n = 366) or AI (n = 403) and a sample of controls (n = 2170) were identified from the Mayo Clinic Mammography Practice and San Francisco Mammography Registry. Volumetric percent density (VPD) and dense breast volume (DV) were measured using Volpara (Matakina Technology) and Quantra (Hologic) software. Linear regression estimated the effect of treatment on annualized changes in density.Results: Premenopausal women using tamoxifen experienced annualized declines in VPD of 1.17% to 1.70% compared with 0.30% to 0.56% for controls and declines in DV of 7.43 to 15.13 cm3 compared with 0.28 to 0.63 cm3 in controls, for Volpara and Quantra, respectively. The greatest reductions were observed among women with ≥10% baseline density. Postmenopausal AI users had greater declines in VPD than controls (Volpara P = 0.02; Quantra P = 0.03), and reductions were greatest among women with ≥10% baseline density. Declines in VPD among postmenopausal women using tamoxifen were only statistically greater than controls when measured with Quantra.Conclusions: Automated software can detect volumetric breast density changes among women on tamoxifen and AI.Impact: If declines in volumetric density predict breast cancer outcomes, these measures may be used as interim prognostic indicators. Cancer Epidemiol Biomarkers Prev; 26(6); 930-7. ©2017 AACR.

Published
2017

31. Validation and functional characterization of GWAS-identified variants for chronic lymphocytic leukemia: a CRuCIAL study

Author

García-Martín, Paloma, Díez, Ana Moñiz, Maldonado, José Manuel Sánchez, Serrano, Antonio José Cabrera, ter Horst, Rob, Benavente, Yolanda, Landi, Stefano, Macauda, Angelica, Clay-Gilmour, Alyssa, Hernández-Mohedo, Francisca, Niazi, Yasmeen, González-Sierra, Pedro, Espinet, Blanca, Rodríguez-Sevilla, Juan José, Maffei, Rossana, Blanco, Gonzalo, Giaccherini, Matteo, Puiggros, Anna, Cerhan, James, Marasca, Roberto, Cañadas-Garre, Marisa, López-Nevot, Miguel Ángel, Chen-Liang, Tzu, Thomsen, Hauke, Gámez, Irene, Moreno, Víctor, Marcos-Gragera, Rafael, García-Álvarez, María, Llorca, Javier, Jerez, Andrés, Berndt, Sonja, Butrym, Aleksandra, Norman, Aaron D., Casabonne, Delphine, Luppi, Mario, Slager, Susan L., Hemminki, Kari, Li, Yang, Alcoceba, Miguel, Campa, Daniele, Canzian, Federico, de Sanjosé, Silvia, Försti, Asta, Netea, Mihai G., Jurado, Manuel, and Sainz, Juan

Published
2022
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33. Genome-wide meta-analysis of monoclonal gammopathy of undetermined significance (MGUS) identifies risk loci impacting IRF-6

Author

Clay-Gilmour, Alyssa, Chattopadhyay, Subhayan, Hildebrandt, Michelle A. T., Thomsen, Hauke, Weinhold, Niels, Vodicka, Pavel, Vodickova, Ludmila, Hoffmann, Per, Nöthen, Markus M., Jöckel, Karl-Heinz, Schmidt, Börge, Langer, Christian, Hajek, Roman, Hallmans, Göran, Pettersson-Kymmer, Ulrika, Ohlsson, Claes, Späth, Florentin, Houlston, Richard, Goldschmidt, Hartmut, Manasanch, Elisabet E., Norman, Aaron, Kumar, Shaji, Rajkumar, S. Vincent, Slager, Susan, Försti, Asta, Vachon, Celine M., and Hemminki, Kari

Published
2022
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35. 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
Health Services and Systems, Biomedical and Clinical Sciences, Health Sciences, Oncology and Carcinogenesis, Breast Cancer, Cancer, Aging, Clinical Research, Adult, Age Factors, Breast Density, Breast Neoplasms, Female, Humans, Mammary Glands, Human, Middle Aged, Radiography, Receptor, ErbB-2, Receptors, Estrogen, Risk Factors, Young Adult, Receptor, erbB-2, Medical and Health Sciences, Epidemiology, Biomedical and clinical sciences, Health sciences
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

36. The contributions of breast density and common genetic variation to breast cancer risk.

Author

Vachon, Celine M, Pankratz, V Shane, Scott, Christopher G, Haeberle, Lothar, Ziv, Elad, Jensen, Matthew R, Brandt, Kathleen R, Whaley, Dana H, Olson, Janet E, Heusinger, Katharina, Hack, Carolin C, Jud, Sebastian M, Beckmann, Matthias W, Schulz-Wendtland, Ruediger, Tice, Jeffrey A, Norman, Aaron D, Cunningham, Julie M, Purrington, Kristen S, Easton, Douglas F, Sellers, Thomas A, Kerlikowske, Karla, Fasching, Peter A, and Couch, Fergus J

Subjects
Breast, Mammary Glands, Human, Humans, Breast Neoplasms, Genetic Predisposition to Disease, Radiography, Area Under Curve, Logistic Models, Odds Ratio, Risk Assessment, Risk Factors, Case-Control Studies, Polymorphism, Single Nucleotide, Adult, Aged, Middle Aged, United States, Germany, Female, Genetic Variation, Breast Density, Clinical Research, Cancer, Breast Cancer, Prevention, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

We evaluated whether a 76-locus polygenic risk score (PRS) and Breast Imaging Reporting and Data System (BI-RADS) breast density were independent risk factors within three studies (1643 case patients, 2397 control patients) using logistic regression models. We incorporated the PRS odds ratio (OR) into the Breast Cancer Surveillance Consortium (BCSC) risk-prediction model while accounting for its attributable risk and compared five-year absolute risk predictions between models using area under the curve (AUC) statistics. All statistical tests were two-sided. BI-RADS density and PRS were independent risk factors across all three studies (P interaction = .23). Relative to those with scattered fibroglandular densities and average PRS (2(nd) quartile), women with extreme density and highest quartile PRS had 2.7-fold (95% confidence interval [CI] = 1.74 to 4.12) increased risk, while those with low density and PRS had reduced risk (OR = 0.30, 95% CI = 0.18 to 0.51). PRS added independent information (P < .001) to the BCSC model and improved discriminatory accuracy from AUC = 0.66 to AUC = 0.69. Although the BCSC-PRS model was well calibrated in case-control data, independent cohort data are needed to test calibration in the general population.

Published
2015

37. Association of polygenic risk score with the risk of chronic lymphocytic leukemia and monoclonal B-cell lymphocytosis

Author

Kleinstern, Geffen, Camp, Nicola J., Goldin, Lynn R., Vachon, Celine M., Vajdic, Claire M., de Sanjose, Silvia, Weinberg, J. Brice, Benavente, Yolanda, Casabonne, Delphine, Liebow, Mark, Nieters, Alexandra, Hjalgrim, Henrik, Melbye, Mads, Glimelius, Bengt, Adami, Hans-Olov, Boffetta, Paolo, Brennan, Paul, Maynadie, Marc, McKay, James, Cocco, Pier Luigi, Shanafelt, Tait D., Call, Timothy G., Norman, Aaron D., Hanson, Curtis, Robinson, Dennis, Chaffee, Kari G., Brooks-Wilson, Angela R., Monnereau, Alain, Clavel, Jacqueline, Glenn, Martha, Curtin, Karen, Conde, Lucia, Bracci, Paige M., Morton, Lindsay M., Cozen, Wendy, Severson, Richard K., Chanock, Stephen J., Spinelli, John J., Johnston, James B., Rothman, Nathaniel, Skibola, Christine F., Leis, Jose F., Kay, Neil E., Smedby, Karin E., Berndt, Sonja I., Cerhan, James R., Caporaso, Neil, and Slager, Susan L.

Published
2018
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38. Mammographic density and risk of breast cancer by age and tumor characteristics

Author

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

Abstract

Abstract Introduction Understanding whether mammographic density (MD) is associated with all breast tumor subtypes and whether the strength of association varies by age is important for utilizing MD in risk models. Methods Data were pooled from six studies including 3414 women with breast cancer and 7199 without who underwent screening mammography. Percent MD was assessed from digitized film-screen mammograms using a computer-assisted threshold technique. We used polytomous logistic regression to calculate breast cancer odds according to tumor type, histopathological characteristics, and receptor (estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor (HER2)) status by age (51%) versus average density (11-25%). Women ages 2.1 cm) versus small tumors and positive versus negative lymph node status (P’s

Published
2013

39. 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
Cancer, Case-Control Studies, Chromosomes, Human, Pair 2, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Leukemia, Lymphocytic, Chronic, B-Cell, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Recombination, Genetic, Risk, Biological Sciences, Medical and Health Sciences, 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

40. Genome-wide association study of germline variants and breast cancer-specific mortality

Author

Escala-Garcia, Maria, Guo, Qi, Dörk, Thilo, Canisius, Sander, Keeman, Renske, Dennis, Joe, Beesley, Jonathan, Lecarpentier, Julie, Bolla, Manjeet K., Wang, Qin, Abraham, Jean, Andrulis, Irene L., Anton-Culver, Hoda, Arndt, Volker, Auer, Paul L., Beckmann, Matthias W., Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Bernstein, Leslie, Blomqvist, Carl, Boeckx, Bram, Bojesen, Stig E., Bonanni, Bernardo, Børresen-Dale, Anne-Lise, Brauch, Hiltrud, Brenner, Hermann, Brentnall, Adam, Brinton, Louise, Broberg, Per, Brock, Ian W., Brucker, Sara Y., Burwinkel, Barbara, Caldas, Carlos, Caldés, Trinidad, Campa, Daniele, Canzian, Federico, Carracedo, Angel, Carter, Brian D., Castelao, Jose E., Chang-Claude, Jenny, Chanock, Stephen J., Chenevix-Trench, Georgia, Cheng, Ting-Yuan David, Chin, Suet-Feung, Clarke, Christine L., NBCS Collaborators, Cordina-Duverger, Emilie, Couch, Fergus J., Cox, David G., Cox, Angela, Cross, Simon S., Czene, Kamila, Daly, Mary B., Devilee, Peter, Dunn, Janet A., Dunning, Alison M., Durcan, Lorraine, Dwek, Miriam, Earl, Helena M., Ekici, Arif B., Eliassen, A. Heather, Ellberg, Carolina, Engel, Christoph, Eriksson, Mikael, Evans, D. Gareth, Figueroa, Jonine, Flesch-Janys, Dieter, Flyger, Henrik, Gabrielson, Marike, Gago-Dominguez, Manuela, Galle, Eva, Gapstur, Susan M., García-Closas, Montserrat, García-Sáenz, José A., Gaudet, Mia M., George, Angela, Georgoulias, Vassilios, Giles, Graham G., Glendon, Gord, Goldgar, David E., González-Neira, Anna, Alnæs, Grethe I. Grenaker, Grip, Mervi, Guénel, Pascal, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A., Håkansson, Niclas, Hall, Per, Hamann, Ute, Hankinson, Susan, Harkness, Elaine F., Harrington, Patricia A., Hart, Steven N., Hartikainen, Jaana M., Hein, Alexander, Hillemanns, Peter, Hiller, Louise, Holleczek, Bernd, Hollestelle, Antoinette, Hooning, Maartje J., Hoover, Robert N., Hopper, John L., Howell, Anthony, Huang, Guanmengqian, Humphreys, Keith, Hunter, David J., Janni, Wolfgang, John, Esther M., Jones, Michael E., Jukkola-Vuorinen, Arja, Jung, Audrey, Kaaks, Rudolf, Kabisch, Maria, Kaczmarek, Katarzyna, Kerin, Michael J., Khan, Sofia, Khusnutdinova, Elza, Kiiski, Johanna I., Kitahara, Cari M., Knight, Julia A., Ko, Yon-Dschun, Koppert, Linetta B., Kosma, Veli-Matti, Kraft, Peter, Kristensen, Vessela N., Krüger, Ute, Kühl, Tabea, Lambrechts, Diether, Le Marchand, Loic, Lee, Eunjung, Lejbkowicz, Flavio, Li, Lian, Lindblom, Annika, Lindström, Sara, Linet, Martha, Lissowska, Jolanta, Lo, Wing-Yee, Loibl, Sibylle, Lubiński, Jan, Lux, Michael P., MacInnis, Robert J., Maierthaler, Melanie, Maishman, Tom, Makalic, Enes, Mannermaa, Arto, Manoochehri, Mehdi, Manoukian, Siranoush, Margolin, Sara, Martinez, Maria Elena, Mavroudis, Dimitrios, McLean, Catriona, Meindl, Alfons, Middha, Pooja, Miller, Nicola, Milne, Roger L., Moreno, Fernando, Mulligan, Anna Marie, Mulot, Claire, Nassir, Rami, Neuhausen, Susan L., Newman, William T., Nielsen, Sune F., Nordestgaard, Børge G., Norman, Aaron, Olsson, Håkan, Orr, Nick, Pankratz, V. Shane, Park-Simon, Tjoung-Won, Perez, Jose I. A., Pérez-Barrios, Clara, Peterlongo, Paolo, Petridis, Christos, Pinchev, Mila, Prajzendanc, Karoliona, Prentice, Ross, Presneau, Nadege, Prokofieva, Darya, Pylkäs, Katri, Rack, Brigitte, Radice, Paolo, Ramachandran, Dhanya, Rennert, Gadi, Rennert, Hedy S., Rhenius, Valerie, Romero, Atocha, Roylance, Rebecca, Saloustros, Emmanouil, Sawyer, Elinor J., Schmidt, Daniel F., Schmutzler, Rita K., Schneeweiss, Andreas, Schoemaker, Minouk J., Schumacher, Fredrick, Schwentner, Lukas, Scott, Rodney J., Scott, Christopher, Seynaeve, Caroline, Shah, Mitul, Simard, Jacques, Smeets, Ann, Sohn, Christof, Southey, Melissa C., Swerdlow, Anthony J., Talhouk, Aline, Tamimi, Rulla M., Tapper, William J., Teixeira, Manuel R., Tengström, Maria, Terry, Mary Beth, Thöne, Kathrin, Tollenaar, Rob A. E. M., Tomlinson, Ian, Torres, Diana, Truong, Thérèse, Turman, Constance, Turnbull, Clare, Ulmer, Hans-Ulrich, Untch, Michael, Vachon, Celine, van Asperen, Christi J., van den Ouweland, Ans M. W., van Veen, Elke M., Wendt, Camilla, Whittemore, Alice S., Willett, Walter, Winqvist, Robert, Wolk, Alicja, Yang, Xiaohong R., Zhang, Yan, Easton, Douglas F., Fasching, Peter A., Nevanlinna, Heli, Eccles, Diana M., Pharoah, Paul D. P., and Schmidt, Marjanka K.

Published
2019
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43. Polymorphisms within Autophagy-Related Genes as Susceptibility Biomarkers for Multiple Myeloma: A Meta-Analysis of Three Large Cohorts and Functional Characterization

Author

Clavero, Esther, primary, Sanchez-Maldonado, José Manuel, additional, Macauda, Angelica, additional, Ter Horst, Rob, additional, Sampaio-Marques, Belém, additional, Jurczyszyn, Artur, additional, Clay-Gilmour, Alyssa, additional, Stein, Angelika, additional, Hildebrandt, Michelle A. T., additional, Weinhold, Niels, additional, Buda, Gabriele, additional, García-Sanz, Ramón, additional, Tomczak, Waldemar, additional, Vogel, Ulla, additional, Jerez, Andrés, additional, Zawirska, Daria, additional, Wątek, Marzena, additional, Hofmann, Jonathan N., additional, Landi, Stefano, additional, Spinelli, John J., additional, Butrym, Aleksandra, additional, Kumar, Abhishek, additional, Martínez-López, Joaquín, additional, Galimberti, Sara, additional, Sarasquete, María Eugenia, additional, Subocz, Edyta, additional, Iskierka-Jażdżewska, Elzbieta, additional, Giles, Graham G., additional, Rybicka-Ramos, Malwina, additional, Kruszewski, Marcin, additional, Abildgaard, Niels, additional, Verdejo, Francisco García, additional, Sánchez Rovira, Pedro, additional, da Silva Filho, Miguel Inacio, additional, Kadar, Katalin, additional, Razny, Małgorzata, additional, Cozen, Wendy, additional, Pelosini, Matteo, additional, Jurado, Manuel, additional, Bhatti, Parveen, additional, Dudzinski, Marek, additional, Druzd-Sitek, Agnieszka, additional, Orciuolo, Enrico, additional, Li, Yang, additional, Norman, Aaron D., additional, Zaucha, Jan Maciej, additional, Reis, Rui Manuel, additional, Markiewicz, Miroslaw, additional, Rodríguez Sevilla, Juan José, additional, Andersen, Vibeke, additional, Jamroziak, Krzysztof, additional, Hemminki, Kari, additional, Berndt, Sonja I., additional, Rajkumar, Vicent, additional, Mazur, Grzegorz, additional, Kumar, Shaji K., additional, Ludovico, Paula, additional, Nagler, Arnon, additional, Chanock, Stephen J., additional, Dumontet, Charles, additional, Machiela, Mitchell J., additional, Varkonyi, Judit, additional, Camp, Nicola J., additional, Ziv, Elad, additional, Vangsted, Annette Juul, additional, Brown, Elizabeth E., additional, Campa, Daniele, additional, Vachon, Celine M., additional, Netea, Mihai G., additional, Canzian, Federico, additional, Försti, Asta, additional, and Sainz, Juan, additional

Published
2023
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44. Do GWAS-Identified Risk Variants for Chronic Lymphocytic Leukemia Influence Overall Patient Survival and Disease Progression?

Author

Cabrera-Serrano, Antonio José, primary, Sánchez-Maldonado, José Manuel, additional, ter Horst, Rob, additional, Macauda, Angelica, additional, García-Martín, Paloma, additional, Benavente, Yolanda, additional, Landi, Stefano, additional, Clay-Gilmour, Alyssa, additional, Niazi, Yasmeen, additional, Espinet, Blanca, additional, Rodríguez-Sevilla, Juan José, additional, Pérez, Eva María, additional, Maffei, Rossana, additional, Blanco, Gonzalo, additional, Giaccherini, Matteo, additional, Cerhan, James R., additional, Marasca, Roberto, additional, López-Nevot, Miguel Ángel, additional, Chen-Liang, Tzu, additional, Thomsen, Hauke, additional, Gámez, Irene, additional, Campa, Daniele, additional, Moreno, Víctor, additional, de Sanjosé, Silvia, additional, Marcos-Gragera, Rafael, additional, García-Álvarez, María, additional, Dierssen-Sotos, Trinidad, additional, Jerez, Andrés, additional, Butrym, Aleksandra, additional, Norman, Aaron D., additional, Luppi, Mario, additional, Slager, Susan L., additional, Hemminki, Kari, additional, Li, Yang, additional, Berndt, Sonja I., additional, Casabonne, Delphine, additional, Alcoceba, Miguel, additional, Puiggros, Anna, additional, Netea, Mihai G., additional, Försti, Asta, additional, Canzian, Federico, additional, and Sainz, Juan, additional

Published
2023
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46. Abstract 5222: Genetic variants associated with progression from monoclonal B-cell lymphocytosis (MBL) to chronic lymphocytic leukemia (CLL)

Author

Mwangi, Raphael, primary, Kleinstern, Geffen, additional, Achenbach, Sara J., additional, Robinson, Dennis, additional, Norman, Aaron D., additional, Rabe, Kari G., additional, Olson, Janet E., additional, Kay, Neil E., additional, Waller, Rosalie G., additional, Boddicker, Nicholas J., additional, Cerhan, James R., additional, Braggio, Esteban, additional, Parikh, Sameer A., additional, Hanson, Curtis A., additional, Vachon, Celine M., additional, Shanafelt, Tait, additional, and Slager, Susan L., additional

Published
2023
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47. Supplementary Figure Legends from Dense and Nondense Mammographic Area and Risk of Breast Cancer by Age and Tumor Characteristics

Author

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

Published
2023
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48. Data from Mapping of the IRF8 Gene Identifies a 3′UTR Variant Associated with Risk of Chronic Lymphocytic Leukemia but not Other Common Non-Hodgkin Lymphoma Subtypes

Author

Slager, Susan L., primary, Achenbach, Sara J., primary, Asmann, Yan W., primary, Camp, Nicola J., primary, Rabe, Kari G., primary, Goldin, Lynn R., primary, Call, Timothy G., primary, Shanafelt, Tait D., primary, Kay, Neil E., primary, Cunningham, Julie M., primary, Wang, Alice H., primary, Weinberg, J. Brice, primary, Norman, Aaron D., primary, Link, Brian K., primary, Leis, Jose F., primary, Vachon, Celine M., primary, Lanasa, Mark C., primary, Caporaso, Neil E., primary, Novak, Anne J., primary, and Cerhan, James R., primary

Published
2023
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49. Supplementary Table 5 from Mapping of the IRF8 Gene Identifies a 3′UTR Variant Associated with Risk of Chronic Lymphocytic Leukemia but not Other Common Non-Hodgkin Lymphoma Subtypes

Author

Slager, Susan L., primary, Achenbach, Sara J., primary, Asmann, Yan W., primary, Camp, Nicola J., primary, Rabe, Kari G., primary, Goldin, Lynn R., primary, Call, Timothy G., primary, Shanafelt, Tait D., primary, Kay, Neil E., primary, Cunningham, Julie M., primary, Wang, Alice H., primary, Weinberg, J. Brice, primary, Norman, Aaron D., primary, Link, Brian K., primary, Leis, Jose F., primary, Vachon, Celine M., primary, Lanasa, Mark C., primary, Caporaso, Neil E., primary, Novak, Anne J., primary, and Cerhan, James R., primary

Published
2023
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50. Supplementary Table 3 from Mapping of the IRF8 Gene Identifies a 3′UTR Variant Associated with Risk of Chronic Lymphocytic Leukemia but not Other Common Non-Hodgkin Lymphoma Subtypes

Author

Slager, Susan L., primary, Achenbach, Sara J., primary, Asmann, Yan W., primary, Camp, Nicola J., primary, Rabe, Kari G., primary, Goldin, Lynn R., primary, Call, Timothy G., primary, Shanafelt, Tait D., primary, Kay, Neil E., primary, Cunningham, Julie M., primary, Wang, Alice H., primary, Weinberg, J. Brice, primary, Norman, Aaron D., primary, Link, Brian K., primary, Leis, Jose F., primary, Vachon, Celine M., primary, Lanasa, Mark C., primary, Caporaso, Neil E., primary, Novak, Anne J., primary, and Cerhan, James R., primary

Published
2023
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