2,827 results on '"Hankinson, Susan E."'
Search Results
2. A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry
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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
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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
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- 2023
3. Birthweight and subsequent risk for thyroid and autoimmune conditions in postmenopausal women
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Monahan, Brian, Farland, Leslie V, Shadyab, Aladdin H, Hankinson, Susan E, Manson, JoAnn E, and Spracklen, Cassandra N
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Reproductive Medicine ,Biomedical and Clinical Sciences ,Autoimmune Disease ,Prevention ,Arthritis ,Aetiology ,2.4 Surveillance and distribution ,Inflammatory and immune system ,Autoimmune Diseases ,Birth Weight ,Female ,Humans ,Postmenopause ,Proportional Hazards Models ,Risk Factors ,Thyroid Diseases ,Birthweight ,thyroid ,autoimmune disease ,lupus ,rheumatoid arthritis ,hyperthyroid ,hypothyroid ,postmenopausal women ,Medical and Health Sciences ,Biomedical and clinical sciences ,Health sciences - Abstract
The objective of this study was to determine the association between birthweight and risk of thyroid and autoimmune conditions in a large sample of postmenopausal women. Baseline data from the Women's Health Initiative (n = 80,806) were used to examine the associations between birthweight category (
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- 2022
4. Prolactin levels and breast cancer risk by tumor expression of prolactin-related markers
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Hathaway, Cassandra A., Rice, Megan S., Collins, Laura C., Chen, Dilys, Frank, David A., Walker, Sarah, Clevenger, Charles V., Tamimi, Rulla M., Tworoger, Shelley S., and Hankinson, Susan E.
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- 2023
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5. BMI and breast cancer risk around age at menopause
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Von Holle, Ann, Adami, Hans-Olov, Baglietto, Laura, Berrington de Gonzalez, Amy, Bertrand, Kimberly A., Blot, William, Chen, Yu, DeHart, Jessica Clague, Dossus, Laure, Eliassen, A. Heather, Fournier, Agnes, Garcia-Closas, Montse, Giles, Graham, Guevara, Marcela, Hankinson, Susan E., Heath, Alicia, Jones, Michael E., Joshu, Corinne E., Kaaks, Rudolf, Kirsh, Victoria A., Kitahara, Cari M., Koh, Woon-Puay, Linet, Martha S., Park, Hannah Lui, Masala, Giovanna, Mellemkjaer, Lene, Milne, Roger L., O'Brien, Katie M., Palmer, Julie R., Riboli, Elio, Rohan, Thomas E., Shrubsole, Martha J., Sund, Malin, Tamimi, Rulla, Tin Tin, Sandar, Visvanathan, Kala, Vermeulen, Roel CH, Weiderpass, Elisabete, Willett, Walter C., Yuan, Jian-Min, Zeleniuch-Jacquotte, Anne, Nichols, Hazel B., Sandler, Dale P., Swerdlow, Anthony J., Schoemaker, Minouk J., and Weinberg, Clarice R.
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- 2024
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6. Biomarkers of phthalates and inflammation: Findings from a subgroup of Women's Health Initiative participants
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Trim, Avery, Hankinson, Susan E, Liu, Simin, Shadyab, Aladdin H, Meliker, Jaymie, Bao, Wei, Luo, Juhua, Liu, Buyun, Manson, JoAnn E, Tinker, Lesley, Bigelow, Carol, and Reeves, Katherine W
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Public Health ,Health Sciences ,Prevention ,Aging ,Clinical Research ,Detection ,screening and diagnosis ,4.1 Discovery and preclinical testing of markers and technologies ,Cancer ,Biomarkers ,Case-Control Studies ,Environmental Exposure ,Environmental Pollutants ,Female ,Humans ,Inflammation ,Phthalic Acids ,Women's Health ,Phthalates ,Epidemiology ,Postmenopausal ,CRP ,IL-6 ,Public Health and Health Services ,Toxicology ,Public health - Abstract
BackgroundRecent experimental work has shown that phthalates may increase inflammation. Prior research has not examined the role of exposure to phthalates in relation to inflammatory status among postmenopausal women who are at higher risk of developing inflammation-related chronic disorders.ObjectivesWe aimed to examine the associations of urinary phthalate biomarker concentrations with circulating levels of c-reactive protein [CRP] and interleukin-6 [IL-6] among 443 postmenopausal women selected into a breast cancer case-control study nested within the Women's Health Initiative (WHI).MethodsA total of 13 phthalate metabolites were measured in urine samples provided at WHI enrollment from 1993 to 1998. We also measured baseline levels of CRP and IL-6 in these women's serum or plasma samples. Multivariable linear models were used to investigate the role of each phthalate biomarker in relation to CRP and IL-6, adjusting for potential confounding factors and specifically evaluating the role of BMI.ResultsIn adjusted models we observed positive associations of monocarboxynonyl phthalate (MCNP) with CRP (β = 0.092; 95% CI 0.026, 0.158) and IL-6 (β = 0.108; 95% CI 0.013, 0.204). These positive associations were attenuated and non-significant, however, after further adjustment for body mass index (BMI). In contrast, we observed inverse associations of monoethyl phthalate (MEP) (β = -0.019; 95% CI -0.036, -0.001) and monobenzyl phthalate (MBzP) (β = -0.034; 95% CI -0.058, -0.010) with CRP levels only after adjustment for BMI. Other phthalate biomarkers examined were not significantly associated with either CRP or IL-6 levels.ConclusionsOverall, these results do not suggest an important role for phthalates in promoting an inflammatory response. Future prospective studies are warranted to improve understanding of these associations, particularly in clarifying the role of BMI.
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- 2021
7. Metabolomic profiles of chronic distress are associated with cardiovascular disease risk and inflammation-related risk factors
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Balasubramanian, Raji, Shutta, Katherine H., Guasch-Ferre, Marta, Huang, Tianyi, Jha, Shaili C., Zhu, Yiwen, Shadyab, Aladdin H., Manson, JoAnn E., Corella, Dolores, Fitó, Montserrat, Hu, Frank B., Rexrode, Kathryn M., Clish, Clary B., Hankinson, Susan E., and Kubzansky, Laura D.
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- 2023
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8. Circulating vitamin D and breast cancer risk: an international pooling project of 17 cohorts
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Visvanathan, Kala, Mondul, Alison M., Zeleniuch-Jacquotte, Anne, Wang, Molin, Gail, Mitchell H., Yaun, Shiaw-Shyuan, Weinstein, Stephanie J., McCullough, Marjorie L., Eliassen, A. Heather, Cook, Nancy R., Agnoli, Claudia, Almquist, Martin, Black, Amanda, Buring, Julie E., Chen, Chu, Chen, Yu, Clendenen, Tess, Dossus, Laure, Fedirko, Veronika, Gierach, Gretchen L., Giovannucci, Edward L., Goodman, Gary E., Goodman, Marc T., Guénel, Pascal, Hallmans, Göran, Hankinson, Susan E., Horst, Ronald L., Hou, Tao, Huang, Wen-Yi, Jones, Michael E., Joshu, Corrine E., Kaaks, Rudolf, Krogh, Vittorio, Kühn, Tilman, Kvaskoff, Marina, Lee, I-Min, Mahamat-Saleh, Yahya, Malm, Johan, Manjer, Jonas, Maskarinec, Gertraud, Millen, Amy E., Mukhtar, Toqir K., Neuhouser, Marian L., Robsahm, Trude E., Schoemaker, Minouk J., Sieri, Sabina, Sund, Malin, Swerdlow, Anthony J., Thomson, Cynthia A., Ursin, Giske, Wactawski-Wende, Jean, Wang, Ying, Wilkens, Lynne R., Wu, Yujie, Zoltick, Emilie, Willett, Walter C., Smith-Warner, Stephanie A., and Ziegler, Regina G.
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- 2023
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9. Assessment of interactions between 205 breast cancer susceptibility loci and 13 established risk factors in relation to breast cancer risk, in the Breast Cancer Association Consortium
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Kapoor, Pooja Middha, Lindström, Sara, Behrens, Sabine, Wang, Xiaoliang, Michailidou, Kyriaki, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Dunning, Alison M, Pharoah, Paul DP, Schmidt, Marjanka K, Kraft, Peter, García-Closas, Montserrat, Easton, Douglas F, Milne, Roger L, Chang-Claude, Jenny, Ahearn, Thomas, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Augustinsson, Annelie, Freeman, Laura E Beane, Beckmann, Matthias W, Benitez, Javier, Bernstein, Leslie, Berrandou, Takiy, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Brock, Ian W, Broeks, Annegien, Brooks-Wilson, Angela, Butterbach, Katja, Cai, Qiuyin, Campa, Daniele, Canzian, Federico, Carter, Brian D, Castelao, Jose E, Chanock, Stephen J, Chenevix-Trench, Georgia, Cheng, Ting-Yuan David, Clarke, Christine L, Cordina-Duverger, Emilie, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dai, James Y, Dite, Gillian S, Earp, H Shelton, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Flyger, Henrik, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, Gapstur, Susan M, Gaudet, Mia M, Giles, Graham G, González-Neira, Anna, Grundy, Anne, Guénel, Pascal, Haeberle, Lothar, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hankinson, Susan E, Harkness, Elaine F, Harstad, Tricia, He, Wei, Heyworth, Jane, Hoover, Robert N, Hopper, John L, Humphreys, Keith, Hunter, David J, Marrón, Pablo Isidro, John, Esther M, Jones, Michael E, Jung, Audrey, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Krüger, Ute, Lambrechts, Diether, Le Marchand, Loic, Lee, Eunjung, Lejbkowicz, Flavio, Linet, Martha, Lissowska, Jolanta, Llaneza, Ana, Lo, Wing-Yee, and Makalic, Enes
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Genetics ,Estrogen ,Clinical Research ,Cancer ,Breast Cancer ,Prevention ,2.1 Biological and endogenous factors ,Aetiology ,Alleles ,Breast Neoplasms ,Case-Control Studies ,Europe ,Factor XIII ,Female ,Gene-Environment Interaction ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Genotype ,Humans ,Polymorphism ,Single Nucleotide ,Receptors ,Estrogen ,Risk Factors ,White People ,Breast Cancer Association Consortium ,Europeans ,Gene-environment interaction ,breast cancer ,epidemiology ,risk factors ,single nucleotide polymorphism ,Statistics ,Public Health and Health Services ,Epidemiology - Abstract
BackgroundPrevious gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions.MethodsAnalyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions.ResultsNoteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth.ConclusionsOverall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.
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- 2020
10. Psychotropic Medication Use and Postmenopausal Breast Cancer Risk
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George, Anna, Sturgeon, Susan R, Hankinson, Susan E, Shadyab, Aladdin H, Wallace, Robert B, and Reeves, Katherine W
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Health Services and Systems ,Biomedical and Clinical Sciences ,Health Sciences ,Oncology and Carcinogenesis ,Cancer ,Breast Cancer ,Clinical Research ,Mental Health ,Prevention ,Aging ,Patient Safety ,Aged ,Breast ,Breast Carcinoma In Situ ,Breast Neoplasms ,Carcinoma ,Ductal ,Breast ,Female ,Follow-Up Studies ,Humans ,Mammography ,Middle Aged ,Postmenopause ,Proportional Hazards Models ,Psychotropic Drugs ,Risk Factors ,United States ,Medical and Health Sciences ,Epidemiology ,Biomedical and clinical sciences ,Health sciences - Abstract
BackgroundPrior studies evaluating psychotropic medications in relation to breast cancer risk are inconsistent and have not separately evaluated invasive and in situ disease.MethodsWe estimated hazard ratios (HR) and 95% confidence intervals (CI) for the association of psychotropic medication use (any, typical antipsychotics, atypical antipsychotics, and lithium) with invasive and in situ breast cancer risk among Women's Health Initiative participants (N = 155,737).ResultsPrevalence of psychotropic medication use was low (n = 642; 0.4%). During an average 14.8 (SD, 6.5) years of follow-up, 10,067 invasive and 2,285 in situ breast tissues were diagnosed. Any psychotropic medication use was not associated with invasive breast cancer risk compared with nonusers (HR, 0.82; 95% CI, 0.57-1.18). In situ breast cancer risk was higher among "typical" antipsychotic medication users compared with nonusers (HR, 2.05; 95% CI, 0.97-4.30).ConclusionsThese findings do not support an association of psychotropic medication use with invasive breast cancer risk. The possible elevation in in situ breast cancer risk associated with "typical" antipsychotics could not be explained by differences in screening mammography utilization and merits further study.ImpactOur findings contribute to knowledge of the safety profile of psychotropic medications and may be useful to clinicians and patients considering use of these medications.
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- 2020
11. Association between urinary phthalate biomarker concentrations and adiposity among postmenopausal women
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Vieyra, Gabriela, Hankinson, Susan E., Oulhote, Youssef, Vandenberg, Laura N., Tinker, Lesley, Manson, JoAnn E., Shadyab, Aladdin H., Thomson, Cynthia A., Bao, Wei, Allison, Matthew, Odegaard, Andrew O., and Reeves, Katherine W.
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- 2023
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12. Psychological distress and metabolomic markers: A systematic review of posttraumatic stress disorder, anxiety, and subclinical distress
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Zhu, Yiwen, Jha, Shaili C., Shutta, Katherine H., Huang, Tianyi, Balasubramanian, Raji, Clish, Clary B., Hankinson, Susan E., and Kubzansky, Laura D.
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- 2022
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13. Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.
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Mavaddat, Nasim, Michailidou, Kyriaki, Dennis, Joe, Lush, Michael, Fachal, Laura, Lee, Andrew, Tyrer, Jonathan P, Chen, Ting-Huei, Wang, Qin, Bolla, Manjeet K, Yang, Xin, Adank, Muriel A, Ahearn, Thomas, Aittomäki, Kristiina, Allen, Jamie, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Auvinen, Päivi, Barrdahl, Myrto, Beane Freeman, Laura E, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Bernstein, Leslie, Blomqvist, Carl, Bogdanova, Natalia V, Bojesen, Stig E, Bonanni, Bernardo, Børresen-Dale, Anne-Lise, Brauch, Hiltrud, Bremer, Michael, Brenner, Hermann, Brentnall, Adam, Brock, Ian W, Brooks-Wilson, Angela, Brucker, Sara Y, Brüning, Thomas, Burwinkel, Barbara, Campa, Daniele, Carter, Brian D, Castelao, Jose E, Chanock, Stephen J, Chlebowski, Rowan, Christiansen, Hans, Clarke, Christine L, Collée, J Margriet, Cordina-Duverger, Emilie, Cornelissen, Sten, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dörk, Thilo, Dos-Santos-Silva, Isabel, Dumont, Martine, Durcan, Lorraine, Dwek, Miriam, Eccles, Diana M, Ekici, Arif B, Eliassen, A Heather, Ellberg, Carolina, Engel, Christoph, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Fletcher, Olivia, Flyger, Henrik, Försti, Asta, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, Gapstur, Susan M, García-Sáenz, José A, Gaudet, Mia M, Georgoulias, Vassilios, Giles, Graham G, Gilyazova, Irina R, Glendon, Gord, Goldberg, Mark S, Goldgar, David E, González-Neira, Anna, Grenaker Alnæs, Grethe I, Grip, Mervi, Gronwald, Jacek, Grundy, Anne, Guénel, Pascal, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hamann, Ute, and Hankinson, Susan E
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ABCTB Investigators ,kConFab/AOCS Investigators ,NBCS Collaborators ,Humans ,Breast Neoplasms ,Genetic Predisposition to Disease ,Receptors ,Estrogen ,Medical History Taking ,Risk Assessment ,Reproducibility of Results ,Age Factors ,Multifactorial Inheritance ,Polymorphism ,Single Nucleotide ,Adult ,Aged ,Aged ,80 and over ,Middle Aged ,Female ,breast ,cancer ,epidemiology ,genetic ,polygenic ,prediction ,risk ,score ,screening ,stratification ,Human Genome ,Cancer ,Genetics ,Clinical Research ,Prevention ,Breast Cancer ,Good Health and Well Being ,Biological Sciences ,Medical and Health Sciences ,Genetics & Heredity - Abstract
Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.
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- 2019
14. Phthalates and bone mineral density: a systematic review
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Heilmann, Nina Z., Reeves, Katherine W., and Hankinson, Susan E.
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- 2022
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15. Association of body mass index and inflammatory dietary pattern with breast cancer pathologic and genomic immunophenotype in the nurses’ health study
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Asad, Sarah, Damicis, Adrienne, Heng, Yujing J., Kananen, Kathryn, Collier, Katharine A., Adams, Elizabeth J., Kensler, Kevin H., Baker, Gabrielle M., Wesolowski, Robert, Sardesai, Sagar, Gatti-Mays, Margaret, Ramaswamy, Bhuvaneswari, Eliassen, A. Heather, Hankinson, Susan E., Tabung, Fred K., Tamimi, Rulla M., and Stover, Daniel G.
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- 2022
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16. Plasma metabolomic profiles associated with chronic distress in women
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Shutta, Katherine H., Balasubramanian, Raji, Huang, Tianyi, Jha, Shaili C., Zeleznik, Oana A., Kroenke, Candyce H., Tinker, Lesley F., Smoller, Jordan W., Casanova, Ramon, Tworoger, Shelley S., Manson, JoAnn E., Clish, Clary B., Rexrode, Kathryn M., Hankinson, Susan E., and Kubzansky, Laura D.
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- 2021
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17. Associations of depression status with plasma levels of candidate lipid and amino acid metabolites: a meta-analysis of individual data from three independent samples of US postmenopausal women
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Huang, Tianyi, Balasubramanian, Raji, Yao, Yubing, Clish, Clary B., Shadyab, Aladdin H., Liu, Buyun, Tworoger, Shelley S., Rexrode, Kathryn M., Manson, JoAnn E., Kubzansky, Laura D., and Hankinson, Susan E.
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- 2021
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18. Accounting for individualized competing mortality risks in estimating postmenopausal breast cancer risk
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Schonberg, Mara A, Li, Vicky W, Eliassen, A Heather, Davis, Roger B, LaCroix, Andrea Z, McCarthy, Ellen P, Rosner, Bernard A, Chlebowski, Rowan T, Hankinson, Susan E, Marcantonio, Edward R, and Ngo, Long H
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Aging ,Prevention ,Cancer ,Behavioral and Social Science ,Breast Cancer ,Good Health and Well Being ,Adult ,Breast Neoplasms ,Cause of Death ,Female ,Follow-Up Studies ,Humans ,Middle Aged ,Models ,Statistical ,Mortality ,Population Surveillance ,Postmenopause ,Prognosis ,Reproducibility of Results ,Risk Assessment ,Risk Factors ,Breast cancer prediction ,Competing risks ,Older ,Clinical Sciences ,Oncology & Carcinogenesis ,Clinical sciences ,Oncology and carcinogenesis - Abstract
PurposeAccurate risk assessment is necessary for decision-making around breast cancer prevention. We aimed to develop a breast cancer prediction model for postmenopausal women that would take into account their individualized competing risk of non-breast cancer death.MethodsWe included 73,066 women who completed the 2004 Nurses' Health Study (NHS) questionnaire (all ≥57 years) and followed participants until May 2014. We considered 17 breast cancer risk factors (health behaviors, demographics, family history, reproductive factors) and 7 risk factors for non-breast cancer death (comorbidities, functional dependency) and mammography use. We used competing risk regression to identify factors independently associated with breast cancer. We validated the final model by examining calibration (expected-to-observed ratio of breast cancer incidence, E/O) and discrimination (c-statistic) using 74,887 subjects from the Women's Health Initiative Extension Study (WHI-ES; all were ≥55 years and followed for 5 years).ResultsWithin 5 years, 1.8 % of NHS participants were diagnosed with breast cancer (vs. 2.0 % in WHI-ES, p = 0.02), and 6.6 % experienced non-breast cancer death (vs. 5.2 % in WHI-ES, p
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- 2016
19. BMI and breast cancer risk around age at menopause
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IRAS OH Epidemiology Chemical Agents, IRAS – One Health Chemical, Von Holle, Ann, Adami, Hans-Olov, Baglietto, Laura, Berrington, Amy, Bertrand, Kimberly A, Blot, William, Chen, Yu, DeHart, Jessica Clague, Dossus, Laure, Eliassen, A Heather, Fournier, Agnes, Garcia-Closas, Montse, Giles, Graham, Guevara, Marcela, Hankinson, Susan E, Heath, Alicia, Jones, Michael E, Joshu, Corinne E, Kaaks, Rudolf, Kirsh, Victoria A, Kitahara, Cari M, Koh, Woon-Puay, Linet, Martha S, Park, Hannah Lui, Masala, Giovanna, Mellemkjaer, Lene, Milne, Roger L, O'Brien, Katie M, Palmer, Julie R, Riboli, Elio, Rohan, Thomas E, Shrubsole, Martha J, Sund, Malin, Tamimi, Rulla, Tin Tin, Sandar, Visvanathan, Kala, Vermeulen, Roel Ch, Weiderpass, Elisabete, Willett, Walter C, Yuan, Jian-Min, Zeleniuch-Jacquotte, Anne, Nichols, Hazel B, Sandler, Dale P, Swerdlow, Anthony J, Schoemaker, Minouk J, Weinberg, Clarice R, IRAS OH Epidemiology Chemical Agents, IRAS – One Health Chemical, Von Holle, Ann, Adami, Hans-Olov, Baglietto, Laura, Berrington, Amy, Bertrand, Kimberly A, Blot, William, Chen, Yu, DeHart, Jessica Clague, Dossus, Laure, Eliassen, A Heather, Fournier, Agnes, Garcia-Closas, Montse, Giles, Graham, Guevara, Marcela, Hankinson, Susan E, Heath, Alicia, Jones, Michael E, Joshu, Corinne E, Kaaks, Rudolf, Kirsh, Victoria A, Kitahara, Cari M, Koh, Woon-Puay, Linet, Martha S, Park, Hannah Lui, Masala, Giovanna, Mellemkjaer, Lene, Milne, Roger L, O'Brien, Katie M, Palmer, Julie R, Riboli, Elio, Rohan, Thomas E, Shrubsole, Martha J, Sund, Malin, Tamimi, Rulla, Tin Tin, Sandar, Visvanathan, Kala, Vermeulen, Roel Ch, Weiderpass, Elisabete, Willett, Walter C, Yuan, Jian-Min, Zeleniuch-Jacquotte, Anne, Nichols, Hazel B, Sandler, Dale P, Swerdlow, Anthony J, Schoemaker, Minouk J, and Weinberg, Clarice R
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- 2024
20. A Plasma Metabolite Score Related to Psychological Distress and Diabetes Risk: A Nested Case-control Study in US Women.
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Huang, Tianyi, Zhu, Yiwen, Shutta, Katherine H, Balasubramanian, Raji, Zeleznik, Oana A, Rexrode, Kathryn M, Clish, Clary B, Sun, Qi, Hu, Frank B, Kubzansky, Laura D, and Hankinson, Susan E
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PSYCHOLOGICAL distress ,PSILOCYBIN ,DIABETES ,GESTATIONAL diabetes ,CASE-control method ,BODY mass index ,HEALTH behavior - Abstract
Context Psychological distress has been linked to diabetes risk. Few population-based, epidemiologic studies have investigated the potential molecular mechanisms (eg, metabolic dysregulation) underlying this association. Objective To evaluate the association between a metabolomic signature for psychological distress and diabetes risk. Methods We conducted a nested case-control study of plasma metabolomics and diabetes risk in the Nurses' Health Study, including 728 women (mean age: 55.2 years) with incident diabetes and 728 matched controls. Blood samples were collected between 1989 and 1990 and incident diabetes was diagnosed between 1992 and 2008. Based on our prior work, we calculated a weighted plasma metabolite-based distress score (MDS) comprised of 19 metabolites. We used conditional logistic regression accounting for matching factors and other diabetes risk factors to estimate odds ratios (OR) and 95% confidence intervals (CI) for diabetes risk according to MDS. Results After adjusting for sociodemographic factors, family history of diabetes, and health behaviors, the OR (95% CI) for diabetes risk across quintiles of the MDS was 1.00 (reference) for Q1, 1.16 (0.77, 1.73) for Q2, 1.30 (0.88, 1.91) for Q3, 1.99 (1.36, 2.92) for Q4, and 2.47 (1.66, 3.67) for Q5. Each SD increase in MDS was associated with 36% higher diabetes risk (95% CI: 1.21, 1.54; P -trend <.0001). This association was moderately attenuated after additional adjustment for body mass index (comparable OR: 1.17; 95% CI: 1.02, 1.35; P -trend =.02). The MDS explained 17.6% of the association between self-reported psychological distress (defined as presence of depression or anxiety symptoms) and diabetes risk (P =.04). Conclusion MDS was significantly associated with diabetes risk in women. These results suggest that differences in multiple lipid and amino acid metabolites may underlie the observed association between psychological distress and diabetes risk. [ABSTRACT FROM AUTHOR]
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- 2024
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21. Association of oral contraceptives and tubal ligation with antimüllerian hormone
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Langton, Christine R., Whitcomb, Brian W., Purdue-Smithe, Alexandra C., Sievert, Lynnette L., Hankinson, Susan E., Manson, JoAnn E., Rosner, Bernard A., and Bertone-Johnson, Elizabeth R.
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- 2021
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22. Plasma Metabolomic Signature of Early Abuse in Middle-Aged Women
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Huang, Tianyi, Zeleznik, Oana A., Roberts, Andrea L., Balasubramanian, Raji, Clish, Clary B., Eliassen, A. Heather, Rexrode, Kathryn M., Tworoger, Shelley S., Hankinson, Susan E., Koenen, Karestan C., and Kubzansky, Laura D.
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- 2022
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23. Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome
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Machiela, Mitchell J, Zhou, Weiyin, Karlins, Eric, Sampson, Joshua N, Freedman, Neal D, Yang, Qi, Hicks, Belynda, Dagnall, Casey, Hautman, Christopher, Jacobs, Kevin B, Abnet, Christian C, Aldrich, Melinda C, Amos, Christopher, Amundadottir, Laufey T, Arslan, Alan A, Beane-Freeman, Laura E, Berndt, Sonja I, Black, Amanda, Blot, William J, Bock, Cathryn H, Bracci, Paige M, Brinton, Louise A, Bueno-de-Mesquita, H Bas, Burdett, Laurie, Buring, Julie E, Butler, Mary A, Canzian, Federico, Carreon, Tania, Chaffee, Kari G, Chang, I-Shou, Chatterjee, Nilanjan, Chen, Chu, Chen, Constance, Chen, Kexin, Chung, Charles C, Cook, Linda S, Bou, Marta Crous, Cullen, Michael, Davis, Faith G, De Vivo, Immaculata, Ding, Ti, Doherty, Jennifer, Duell, Eric J, Epstein, Caroline G, Fan, Jin-Hu, Figueroa, Jonine D, Fraumeni, Joseph F, Friedenreich, Christine M, Fuchs, Charles S, Gallinger, Steven, Gao, Yu-Tang, Gapstur, Susan M, Garcia-Closas, Montserrat, Gaudet, Mia M, Gaziano, J Michael, Giles, Graham G, Gillanders, Elizabeth M, Giovannucci, Edward L, Goldin, Lynn, Goldstein, Alisa M, Haiman, Christopher A, Hallmans, Goran, Hankinson, Susan E, Harris, Curtis C, Henriksson, Roger, Holly, Elizabeth A, Hong, Yun-Chul, Hoover, Robert N, Hsiung, Chao A, Hu, Nan, Hu, Wei, Hunter, David J, Hutchinson, Amy, Jenab, Mazda, Johansen, Christoffer, Khaw, Kay-Tee, Kim, Hee Nam, Kim, Yeul Hong, Kim, Young Tae, Klein, Alison P, Klein, Robert, Koh, Woon-Puay, Kolonel, Laurence N, Kooperberg, Charles, Kraft, Peter, Krogh, Vittorio, Kurtz, Robert C, LaCroix, Andrea, Lan, Qing, Landi, Maria Teresa, Le Marchand, Loic, Li, Donghui, Liang, Xiaolin, Liao, Linda M, Lin, Dongxin, Liu, Jianjun, Lissowska, Jolanta, Lu, Lingeng, Magliocco, Anthony M, and Malats, Nuria
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- 2016
24. Performance of the Breast Cancer Risk Assessment Tool Among Women Aged 75 Years and Older
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Schonberg, Mara A, Li, Vicky W, Eliassen, A Heather, Davis, Roger B, LaCroix, Andrea Z, McCarthy, Ellen P, Rosner, Bernard A, Chlebowski, Rowan T, Rohan, Thomas E, Hankinson, Susan E, Marcantonio, Edward R, and Ngo, Long H
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Prevention ,Aging ,Breast Cancer ,Clinical Research ,Human Genome ,Genetics ,Cancer ,Good Health and Well Being ,Age Factors ,Aged ,Aged ,80 and over ,Breast Neoplasms ,Cause of Death ,Early Detection of Cancer ,Female ,Follow-Up Studies ,Humans ,Incidence ,Mammography ,Mass Screening ,Middle Aged ,Models ,Statistical ,Odds Ratio ,Risk Assessment ,Risk Factors ,United States ,Whites ,Women's Health ,White People ,Oncology & Carcinogenesis ,Oncology and carcinogenesis - Abstract
BackgroundThe Breast Cancer Risk Assessment Tool (BCRAT, "Gail model") is commonly used for breast cancer prediction; however, it has not been validated for women age 75 years and older.MethodsWe used Nurses' Health Study (NHS) data beginning in 2004 and Women's Health Initiative (WHI) data beginning in 2005 to compare BCRAT's performance among women age 75 years and older with that in women age 55 to 74 years in predicting five-year breast cancer incidence. BCRAT risk factors include: age, race/ethnicity, age at menarche, age at first birth, family history, history of benign breast biopsy, and atypia. We examined BCRAT's calibration by age by comparing expected/observed (E/O) ratios of breast cancer incidence. We examined discrimination by computing c-statistics for the model by age. All statistical tests were two-sided.ResultsSeventy-three thousand seventy-two NHS and 97 081 WHI women participated. NHS participants were more likely to be non-Hispanic white (96.2% vs 84.7% in WHI, P < .001) and were less likely to develop breast cancer (1.8% vs 2.0%, P = .02). E/O ratios by age in NHS were 1.16 (95% confidence interval [CI] = 1.09 to 1.23, age 57-74 years) and 1.31 (95% CI = 1.18 to 1.45, age ≥ 75 years, P = .02), and in WHI 1.03 (95% CI = 0.97 to 1.09, age 55-74 years) and 1.10 (95% CI = 1.00 to 1.21, age ≥ 75 years, P = .21). E/O ratio 95% confidence intervals crossed one among women age 75 years and older when samples were limited to women who underwent mammography and were without significant illness. C-statistics ranged between 0.56 and 0.58 in both cohorts regardless of age.ConclusionsBCRAT accurately predicted breast cancer for women age 75 years and older who underwent mammography and were without significant illness but had modest discrimination. Models that consider individual competing risks of non-breast cancer death may improve breast cancer risk prediction for older women.
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- 2016
25. Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels.
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Kilpeläinen, Tuomas O, Carli, Jayne F Martin, Skowronski, Alicja A, Sun, Qi, Kriebel, Jennifer, Feitosa, Mary F, Hedman, Åsa K, Drong, Alexander W, Hayes, James E, Zhao, Jinghua, Pers, Tune H, Schick, Ursula, Grarup, Niels, Kutalik, Zoltán, Trompet, Stella, Mangino, Massimo, Kristiansson, Kati, Beekman, Marian, Lyytikäinen, Leo-Pekka, Eriksson, Joel, Henneman, Peter, Lahti, Jari, Tanaka, Toshiko, Luan, Jian'an, Del Greco M, Fabiola, Pasko, Dorota, Renström, Frida, Willems, Sara M, Mahajan, Anubha, Rose, Lynda M, Guo, Xiuqing, Liu, Yongmei, Kleber, Marcus E, Pérusse, Louis, Gaunt, Tom, Ahluwalia, Tarunveer S, Ju Sung, Yun, Ramos, Yolande F, Amin, Najaf, Amuzu, Antoinette, Barroso, Inês, Bellis, Claire, Blangero, John, Buckley, Brendan M, Böhringer, Stefan, I Chen, Yii-Der, de Craen, Anton JN, Crosslin, David R, Dale, Caroline E, Dastani, Zari, Day, Felix R, Deelen, Joris, Delgado, Graciela E, Demirkan, Ayse, Finucane, Francis M, Ford, Ian, Garcia, Melissa E, Gieger, Christian, Gustafsson, Stefan, Hallmans, Göran, Hankinson, Susan E, Havulinna, Aki S, Herder, Christian, Hernandez, Dena, Hicks, Andrew A, Hunter, David J, Illig, Thomas, Ingelsson, Erik, Ioan-Facsinay, Andreea, Jansson, John-Olov, Jenny, Nancy S, Jørgensen, Marit E, Jørgensen, Torben, Karlsson, Magnus, Koenig, Wolfgang, Kraft, Peter, Kwekkeboom, Joanneke, Laatikainen, Tiina, Ladwig, Karl-Heinz, LeDuc, Charles A, Lowe, Gordon, Lu, Yingchang, Marques-Vidal, Pedro, Meisinger, Christa, Menni, Cristina, Morris, Andrew P, Myers, Richard H, Männistö, Satu, Nalls, Mike A, Paternoster, Lavinia, Peters, Annette, Pradhan, Aruna D, Rankinen, Tuomo, Rasmussen-Torvik, Laura J, Rathmann, Wolfgang, Rice, Treva K, Brent Richards, J, Ridker, Paul M, Sattar, Naveed, and Savage, David B
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Adipose Tissue ,Animals ,Mice ,Leptin ,RNA ,Messenger ,Tissue Culture Techniques ,Gene Expression Regulation ,Male ,Genome-Wide Association Study ,Gene Knockdown Techniques ,RNA ,Messenger - Abstract
Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P
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- 2016
26. A Plasma Metabolite Score Related to Psychological Distress and Diabetes Risk: A Nested Case-control Study in US Women
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Huang, Tianyi, primary, Zhu, Yiwen, additional, Shutta, Katherine H, additional, Balasubramanian, Raji, additional, Zeleznik, Oana A, additional, Rexrode, Kathryn M, additional, Clish, Clary B, additional, Sun, Qi, additional, Hu, Frank B, additional, Kubzansky, Laura D, additional, and Hankinson, Susan E, additional
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- 2023
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27. International Pooled Analysis of Leisure-Time Physical Activity and Premenopausal Breast Cancer in Women From 19 Cohorts
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Timmins, Iain R., primary, Jones, Michael E., additional, O'Brien, Katie M., additional, Adami, Hans-Olov, additional, Aune, Dagfinn, additional, Baglietto, Laura, additional, Bertrand, Kimberly A., additional, Brantley, Kristen D., additional, Chen, Yu, additional, Clague DeHart, Jessica, additional, Clendenen, Tess V., additional, Dossus, Laure, additional, Eliassen, A. Heather, additional, Fletcher, Olivia, additional, Fournier, Agnès, additional, Håkansson, Niclas, additional, Hankinson, Susan E., additional, Houlston, Richard S., additional, Joshu, Corinne E., additional, Kirsh, Victoria A., additional, Kitahara, Cari M., additional, Koh, Woon-Puay, additional, Linet, Martha S., additional, Park, Hannah Lui, additional, Lynch, Brigid M., additional, May, Anne M., additional, Mellemkjær, Lene, additional, Milne, Roger L., additional, Palmer, Julie R., additional, Ricceri, Fulvio, additional, Rohan, Thomas E., additional, Ruddy, Kathryn J., additional, Sánchez, Maria-Jose, additional, Shu, Xiao-Ou, additional, Smith-Byrne, Karl, additional, Steindorf, Karen, additional, Sund, Malin, additional, Vachon, Celine M., additional, Vatten, Lars J., additional, Visvanathan, Kala, additional, Weiderpass, Elisabete, additional, Willett, Walter C., additional, Wolk, Alicja, additional, Yuan, Jian-Min, additional, Zheng, Wei, additional, Nichols, Hazel B., additional, Sandler, Dale P., additional, Swerdlow, Anthony J., additional, and Schoemaker, Minouk J., additional
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- 2023
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28. Circulating lipids, mammographic density, and risk of breast cancer in the Nurses’ Health Study and Nurses’ Health Study II
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Lucht, Sarah A., Eliassen, A. Heather, Bertrand, Kimberly A., Ahern, Thomas P., Borgquist, Signe, Rosner, Bernard, Hankinson, Susan E., and Tamimi, Rulla M.
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- 2019
29. The Mind–Body Study : study design and reproducibility and interrelationships of psychosocial factors in the Nurses’ Health Study II
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Huang, Tianyi, Trudel-Fitzgerald, Claudia, Poole, Elizabeth M., Sawyer, Sherylin, Kubzansky, Laura D., Hankinson, Susan E., Okereke, Olivia I., and Tworoger, Shelley S.
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- 2019
30. Short-term weight gain and breast cancer risk by hormone receptor classification among pre- and postmenopausal women
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Rosner, Bernard, Eliassen, A Heather, Toriola, Adetunji T, Hankinson, Susan E, Willett, Walter C, Natarajan, Loki, and Colditz, Graham A
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Prevention ,Obesity ,Estrogen ,Clinical Research ,Breast Cancer ,Nutrition ,Cancer ,Aging ,Contraception/Reproduction ,Algorithms ,Breast Neoplasms ,Cohort Studies ,Female ,Humans ,Incidence ,Middle Aged ,Postmenopause ,Premenopause ,Receptors ,Estrogen ,Receptors ,Progesterone ,Risk Factors ,Time Factors ,Weight Gain ,Breast cancer risk ,Hormone receptor classification ,BMI ,Clinical Sciences ,Oncology & Carcinogenesis ,Clinical sciences ,Oncology and carcinogenesis - Abstract
Obesity is well established as a cause of postmenopausal breast cancer incidence and mortality. In contrast, adiposity in early life reduces breast cancer incidence. However, whether short-term weight change influences breast cancer risk is not well known. We followed a cohort of 77,232 women from 1980 to 2006 (1,445,578 person-years), with routinely updated risk factor information, documenting 4196 incident cases of invasive breast cancer. ER and PR status were obtained from pathology reports and medical records yielding a total of 2033 ER+/PR+ tumors, 595 ER-/PR- tumors, 512 ER+/PR- tumors. The log incidence breast cancer model was used to assess the association of short-term weight gain (over past 4 years) while controlling for average BMI before and after menopause. Short-term weight change was significantly associated with breast cancer risk (RR 1.20; 95 % CI 1.09-1.33) for a 4-year weight gain of ≥15 lbs versus no change (≤5 lbs) (P_trend < 0.001). The association was stronger for premenopausal women (RR 1.38; 95 % CI 1.13-1.69) (P_trend = 0.004) than for postmenopausal women (RR 1.10; 95 % CI 0.97-1.25) (P_trend = 0.063). Short-term weight gain during premenopause had a stronger association for ER+/PR- (RR per 25 lb weight gain = 2.19; 95 % CI 1.33-3.61, P = 0.002) and ER-/PR- breast cancer (RR per 25 lb weight gain = 1.61; 95 % CI 1.09-2.38, P = 0.016) than for ER+/PR+ breast cancer (RR per 25 lb weight gain = 1.13; 95 % CI 0.89-1.43, P = 0.32). There are deleterious effects of short-term weight gain, particularly during pre-menopause, even after controlling for average BMI before and after menopause. The association was stronger for ER+/PR- and ER-/PR- than for ER+/PR+ breast cancer.
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- 2015
31. Characterization of Large Structural Genetic Mosaicism in Human Autosomes
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Machiela, Mitchell J, Zhou, Weiyin, Sampson, Joshua N, Dean, Michael C, Jacobs, Kevin B, Black, Amanda, Brinton, Louise A, Chang, I-Shou, Chen, Chu, Chen, Constance, Chen, Kexin, Cook, Linda S, Bou, Marta Crous, De Vivo, Immaculata, Doherty, Jennifer, Friedenreich, Christine M, Gaudet, Mia M, Haiman, Christopher A, Hankinson, Susan E, Hartge, Patricia, Henderson, Brian E, Hong, Yun-Chul, Hosgood, H Dean, Hsiung, Chao A, Hu, Wei, Hunter, David J, Jessop, Lea, Kim, Hee Nam, Kim, Yeul Hong, Kim, Young Tae, Klein, Robert, Kraft, Peter, Lan, Qing, Lin, Dongxin, Liu, Jianjun, Le Marchand, Loic, Liang, Xiaolin, Lissowska, Jolanta, Lu, Lingeng, Magliocco, Anthony M, Matsuo, Keitaro, Olson, Sara H, Orlow, Irene, Park, Jae Yong, Pooler, Loreall, Prescott, Jennifer, Rastogi, Radhai, Risch, Harvey A, Schumacher, Fredrick, Seow, Adeline, Setiawan, Veronica Wendy, Shen, Hongbing, Sheng, Xin, Shin, Min-Ho, Shu, Xiao-Ou, Berg, David VanDen, Wang, Jiu-Cun, Wentzensen, Nicolas, Wong, Maria Pik, Wu, Chen, Wu, Tangchun, Wu, Yi-Long, Xia, Lucy, Yang, Hannah P, Yang, Pan-Chyr, Zheng, Wei, Zhou, Baosen, Abnet, Christian C, Albanes, Demetrius, Aldrich, Melinda C, Amos, Christopher, Amundadottir, Laufey T, Berndt, Sonja I, Blot, William J, Bock, Cathryn H, Bracci, Paige M, Burdett, Laurie, Buring, Julie E, Butler, Mary A, Carreón, Tania, Chatterjee, Nilanjan, Chung, Charles C, Cook, Michael B, Cullen, Michael, Davis, Faith G, Ding, Ti, Duell, Eric J, Epstein, Caroline G, Fan, Jin-Hu, Figueroa, Jonine D, Fraumeni, Joseph F, Freedman, Neal D, Fuchs, Charles S, Gao, Yu-Tang, Gapstur, Susan M, Patiño-Garcia, Ana, Garcia-Closas, Montserrat, Gaziano, J Michael, Giles, Graham G, and Gillanders, Elizabeth M
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Biological Sciences ,Genetics ,Human Genome ,Clinical Research ,2.1 Biological and endogenous factors ,Aetiology ,Aged ,Chromosome Aberrations ,Female ,Genome ,Human ,Genome-Wide Association Study ,Genotype ,Humans ,Male ,Middle Aged ,Mosaicism ,Neoplasms ,Medical and Health Sciences ,Genetics & Heredity ,Biological sciences ,Biomedical and clinical sciences ,Health sciences - Abstract
Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 × 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population.
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- 2015
32. International Pooled Analysis of Leisure-Time Physical Activity and Premenopausal Breast Cancer in Women From 19 Cohorts.
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Timmins, Iain R., Jones, Michael E., O'Brien, Katie M., Adami, Hans-Olov, Aune, Dagfinn, Baglietto, Laura, Bertrand, Kimberly A., Brantley, Kristen D., Chen, Yu, Clague DeHart, Jessica, Clendenen, Tess V., Dossus, Laure, Eliassen, A. Heather, Fletcher, Olivia, Fournier, Agnès, Håkansson, Niclas, Hankinson, Susan E., Houlston, Richard S., Joshu, Corinne E., and Kirsh, Victoria A.
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- 2024
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33. Menstrual cycle characteristics and steroid hormone, prolactin, and growth factor levels in premenopausal women
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Farland, Leslie V., Mu, Fan, Eliassen, A. Heather, Hankinson, Susan E., Tworoger, Shelley S., Barbieri, Robert L., Dowsett, Mitch, Pollak, Michael N., and Missmer, Stacey A.
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- 2017
34. Plasma Estradiol and Testosterone Levels and Ischemic Stroke in Postmenopausal Women
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Hu, Jie, Lin, Jennifer H., Jiménez, Monik C., Manson, JoAnn E., Hankinson, Susan E., and Rexrode, Kathryn M.
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- 2020
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35. A genome-wide association study of early menopause and the combined impact of identified variants
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Perry, John RB, Corre, Tanguy, Esko, Tõnu, Chasman, Daniel I, Fischer, Krista, Franceschini, Nora, He, Chunyan, Kutalik, Zoltan, Mangino, Massimo, Rose, Lynda M, Smith, Albert Vernon, Stolk, Lisette, Sulem, Patrick, Weedon, Michael N, Zhuang, Wei V, Arnold, Alice, Ashworth, Alan, Bergmann, Sven, Buring, Julie E, Burri, Andrea, Chen, Constance, Cornelis, Marilyn C, Couper, David J, Goodarzi, Mark O, Gudnason, Vilmundur, Harris, Tamara, Hofman, Albert, Jones, Michael, Kraft, Peter, Launer, Lenore, Laven, Joop SE, Li, Guo, McKnight, Barbara, Masciullo, Corrado, Milani, Lili, Orr, Nicholas, Psaty, Bruce M, Ridker, Paul M, Rivadeneira, Fernando, Sala, Cinzia, Salumets, Andres, Schoemaker, Minouk, Traglia, Michela, Waeber, Gérard, Chanock, Stephen J, Demerath, Ellen W, Garcia, Melissa, Hankinson, Susan E, Hu, Frank B, Hunter, David J, Lunetta, Kathryn L, Metspalu, Andres, Montgomery, Grant W, Murabito, Joanne M, Newman, Anne B, Ong, Ken K, Spector, Tim D, Stefansson, Kari, Swerdlow, Anthony J, Thorsteinsdottir, Unnur, Van Dam, Rob M, Uitterlinden, André G, Visser, Jenny A, Vollenweider, Peter, Toniolo, Daniela, and Murray, Anna
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Biotechnology ,Contraception/Reproduction ,Infertility ,Genetics ,Human Genome ,Aging ,Estrogen ,Prevention ,Aetiology ,2.1 Biological and endogenous factors ,Reproductive health and childbirth ,Good Health and Well Being ,Case-Control Studies ,Female ,Gene Frequency ,Genome-Wide Association Study ,Humans ,Menopause ,Premature ,Polymorphism ,Single Nucleotide ,Primary Ovarian Insufficiency ,Quantitative Trait Loci ,Risk ,ReproGen Consortium ,Biological Sciences ,Medical and Health Sciences ,Genetics & Heredity - Abstract
Early menopause (EM) affects up to 10% of the female population, reducing reproductive lifespan considerably. Currently, it constitutes the leading cause of infertility in the western world, affecting mainly those women who postpone their first pregnancy beyond the age of 30 years. The genetic aetiology of EM is largely unknown in the majority of cases. We have undertaken a meta-analysis of genome-wide association studies (GWASs) in 3493 EM cases and 13 598 controls from 10 independent studies. No novel genetic variants were discovered, but the 17 variants previously associated with normal age at natural menopause as a quantitative trait (QT) were also associated with EM and primary ovarian insufficiency (POI). Thus, EM has a genetic aetiology which overlaps variation in normal age at menopause and is at least partly explained by the additive effects of the same polygenic variants. The combined effect of the common variants captured by the single nucleotide polymorphism arrays was estimated to account for ∼30% of the variance in EM. The association between the combined 17 variants and the risk of EM was greater than the best validated non-genetic risk factor, smoking.
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- 2013
36. A genome-wide association study to identify genetic susceptibility loci that modify ductal and lobular postmenopausal breast cancer risk associated with menopausal hormone therapy use: a two-stage design with replication
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Hein, Rebecca, Flesch-Janys, Dieter, Dahmen, Norbert, Beckmann, Lars, Lindström, Sara, Schoof, Nils, Czene, Kamila, Mittelstraß, Kirstin, Illig, Thomas, Seibold, Petra, Behrens, Sabine, Humphreys, Keith, Li, Jingmei, Liu, Jianjun, Olson, Janet E, Wang, Xianshu, Hankinson, Susan E, Truong, Thérèse, Menegaux, Florence, dos Santos Silva, Isabel, Johnson, Nichola, The GENICA Network, Chen, Shou-Tung, Yu, Jyh-Cherng, Ziogas, Argyrios, Kataja, Vesa, Kosma, Veli-Matti, Mannermaa, Arto, Anton-Culver, Hoda, Shen, Chen-Yang, Brauch, Hiltrud, Peto, Julian, Guénel, Pascal, Kraft, Peter, Couch, Fergus J, Easton, Douglas F, Hall, Per, and Chang-Claude, Jenny
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Cancer ,Aging ,Prevention ,Breast Cancer ,Genetics ,Human Genome ,Aetiology ,2.1 Biological and endogenous factors ,Breast Neoplasms ,Carcinoma ,Ductal ,Breast ,Carcinoma ,Lobular ,Case-Control Studies ,Chromosomes ,Human ,Estrogen Replacement Therapy ,Estrogens ,Female ,Genetic Loci ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Humans ,Linkage Disequilibrium ,Polymorphism ,Single Nucleotide ,Postmenopause ,Progestins ,Risk Factors ,Sequence Analysis ,DNA ,Postmenopausal breast cancer risk ,Menopausal hormone therapy ,Polymorphisms ,Gene-environment interaction ,Genome-wide association study ,Case-only study ,GENICA Network ,Clinical Sciences ,Oncology and Carcinogenesis ,Oncology & Carcinogenesis - Abstract
Menopausal hormone therapy (MHT) is associated with an elevated risk of breast cancer in postmenopausal women. To identify genetic loci that modify breast cancer risk related to MHT use in postmenopausal women, we conducted a two-stage genome-wide association study (GWAS) with replication. In stage I, we performed a case-only GWAS in 731 invasive breast cancer cases from the German case-control study Mammary Carcinoma Risk Factor Investigation (MARIE). The 1,200 single nucleotide polymorphisms (SNPs) showing the lowest P values for interaction with current MHT use (within 6 months prior to breast cancer diagnosis), were carried forward to stage II, involving pooled case-control analyses including additional MARIE subjects (1,375 cases, 1,974 controls) as well as 795 cases and 764 controls of a Swedish case-control study. A joint P value was calculated for a combined analysis of stages I and II. Replication of the most significant interaction of the combined stage I and II was performed using 5,795 cases and 5,390 controls from nine studies of the Breast Cancer Association Consortium (BCAC). The combined stage I and II yielded five SNPs on chromosomes 2, 7, and 18 with joint P values
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- 2013
37. Polymorphisms in genes related to one-carbon metabolism are not related to pancreatic cancer in PanScan and PanC4
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Leenders, Max, Bhattacharjee, Samsiddhi, Vineis, Paolo, Stevens, Victoria, Bueno-de-Mesquita, H Bas, Shu, Xiao-Ou, Amundadottir, Laufey, Gross, Myron, Tobias, Geoffrey S, Wactawski-Wende, Jean, Arslan, Alan A, Duell, Eric J, Fuchs, Charles S, Gallinger, Steven, Hartge, Patricia, Hoover, Robert N, Holly, Elizabeth A, Jacobs, Eric J, Klein, Alison P, Kooperberg, Charles, LaCroix, Andrea, Li, Donghui, Mandelson, Margaret T, Olson, Sara H, Petersen, Gloria, Risch, Harvey A, Yu, Kai, Wolpin, Brian M, Zheng, Wei, Agalliu, Ilir, Albanes, Demetrius, Boutron-Ruault, Marie-Christine, Bracci, Paige M, Buring, Julie E, Canzian, Federico, Chang, Kenneth, Chanock, Stephen J, Cotterchio, Michelle, Gaziano, J Michael, Giovanucci, Edward L, Goggins, Michael, Hallmans, Göran, Hankinson, Susan E, Hoffman-Bolton, Judith A, Hunter, David J, Hutchinson, Amy, Jacobs, Kevin B, Jenab, Mazda, Khaw, Kay-Tee, Kraft, Peter, Krogh, Vittorio, Kurtz, Robert C, McWilliams, Robert R, Mendelsohn, Julie B, Patel, Alpa V, Rabe, Kari G, Riboli, Elio, Tjønneland, Anne, Trichopoulos, Dimitrios, Virtamo, Jarmo, Visvanathan, Kala, Elena, Joanne W, Yu, Herbert, Zeleniuch-Jacquotte, Anne, and Stolzenberg-Solomon, Rachael Z
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Epidemiology ,Biomedical and Clinical Sciences ,Health Sciences ,Oncology and Carcinogenesis ,Cancer ,Digestive Diseases ,Genetics ,Pancreatic Cancer ,Prevention ,Rare Diseases ,Aetiology ,2.1 Biological and endogenous factors ,Carbon ,Case-Control Studies ,Cohort Studies ,Germ-Line Mutation ,Humans ,Pancreatic Neoplasms ,Polymorphism ,Single Nucleotide ,United States ,Pancreatic cancer ,One-carbon metabolism ,Polymorphisms ,Biomarkers ,Public Health and Health Services ,Oncology and carcinogenesis - Abstract
PurposeThe evidence of a relation between folate intake and one-carbon metabolism (OCM) with pancreatic cancer (PanCa) is inconsistent. In this study, the association between genes and single-nucleotide polymorphisms (SNPs) related to OCM and PanCa was assessed.MethodsUsing biochemical knowledge of the OCM pathway, we identified thirty-seven genes and 834 SNPs to examine in association with PanCa. Our study included 1,408 cases and 1,463 controls nested within twelve cohorts (PanScan). The ten SNPs and five genes with lowest p values (
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- 2013
38. Posttraumatic stress disorder and development of premenstrual syndrome in a longitudinal cohort of women
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Jung, Sun Jae, Roberts, Andrea L., Chocano-Bedoya, Patricia, Whitcomb, Brian W., Missmer, Stacey A., Manson, JoAnn E., Hankinson, Susan E., Bertone-Johnson, Elizabeth R., and Koenen, Karestan C.
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- 2019
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39. Plasma B-vitamins and one-carbon metabolites and the risk of breast cancer in younger women
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Houghton, Serena C., Eliassen, A. Heather, Zhang, Shumin M., Selhub, Jacob, Rosner, Bernard A., Willett, Walter C., and Hankinson, Susan E.
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- 2019
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40. Pre-diagnostic sex hormone levels and survival among breast cancer patients
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Kensler, Kevin H., Eliassen, A. Heather, Rosner, Bernard A., Hankinson, Susan E., Brown, Myles, and Tamimi, Rulla M.
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- 2019
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41. Molecular mechanisms linking high body mass index to breast cancer etiology in post-menopausal breast tumor and tumor-adjacent tissues
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Heng, Yujing J., Wang, Jun, Ahearn, Thomas U., Brown, Susan B., Zhang, Xuehong, Ambrosone, Christine B., de Andrade, Victor Piana, Brufsky, Adam M., Couch, Fergus J., King, Tari A., Modugno, Francesmary, Vachon, Celine M., DuPre, Natalie C., Garcia-Closas, Montserrat, Troester, Melissa A., Hunter, David J., Eliassen, A. Heather, Tamimi, Rulla M., Hankinson, Susan E., and Beck, Andrew H.
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- 2019
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42. A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11
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Siddiq, Afshan, Couch, Fergus J, Chen, Gary K, Lindström, Sara, Eccles, Diana, Millikan, Robert C, Michailidou, Kyriaki, Stram, Daniel O, Beckmann, Lars, Rhie, Suhn Kyong, Ambrosone, Christine B, Aittomäki, Kristiina, Amiano, Pilar, Apicella, Carmel, Investigators, Australian Breast Cancer Tissue Bank, Baglietto, Laura, Bandera, Elisa V, Beckmann, Matthias W, Berg, Christine D, Bernstein, Leslie, Blomqvist, Carl, Brauch, Hiltrud, Brinton, Louise, Bui, Quang M, Buring, Julie E, Buys, Saundra S, Campa, Daniele, Carpenter, Jane E, Chasman, Daniel I, Chang-Claude, Jenny, Chen, Constance, Clavel-Chapelon, Françoise, Cox, Angela, Cross, Simon S, Czene, Kamila, Deming, Sandra L, Diasio, Robert B, Diver, W Ryan, Dunning, Alison M, Durcan, Lorraine, Ekici, Arif B, Fasching, Peter A, Study, Familial Breast Cancer, Feigelson, Heather Spencer, Fejerman, Laura, Figueroa, Jonine D, Fletcher, Olivia, Flesch-Janys, Dieter, Gaudet, Mia M, Consortium, The GENICA, Gerty, Susan M, Rodriguez-Gil, Jorge L, Giles, Graham G, van Gils, Carla H, Godwin, Andrew K, Graham, Nikki, Greco, Dario, Hall, Per, Hankinson, Susan E, Hartmann, Arndt, Hein, Rebecca, Heinz, Judith, Hoover, Robert N, Hopper, John L, Hu, Jennifer J, Huntsman, Scott, Ingles, Sue A, Irwanto, Astrid, Isaacs, Claudine, Jacobs, Kevin B, John, Esther M, Justenhoven, Christina, Kaaks, Rudolf, Kolonel, Laurence N, Coetzee, Gerhard A, Lathrop, Mark, Le Marchand, Loic, Lee, Adam M, Lee, I-Min, Lesnick, Timothy, Lichtner, Peter, Liu, Jianjun, Lund, Eiliv, Makalic, Enes, Martin, Nicholas G, McLean, Catriona A, Meijers-Heijboer, Hanne, Meindl, Alfons, Miron, Penelope, Monroe, Kristine R, Montgomery, Grant W, Müller-Myhsok, Bertram, Nickels, Stefan, Nyante, Sarah J, Olswold, Curtis, Overvad, Kim, Palli, Domenico, Park, Daniel J, Palmer, Julie R, and Pathak, Harsh
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Biological Sciences ,Genetics ,Clinical Research ,Aging ,Human Genome ,Breast Cancer ,Cancer ,Aetiology ,2.1 Biological and endogenous factors ,Breast Neoplasms ,Female ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Humans ,Polymorphism ,Single Nucleotide ,Receptors ,Estrogen ,Australian Breast Cancer Tissue Bank Investigators ,Familial Breast Cancer Study ,GENICA Consortium ,Medical and Health Sciences ,Genetics & Heredity - Abstract
Genome-wide association studies (GWAS) of breast cancer defined by hormone receptor status have revealed loci contributing to susceptibility of estrogen receptor (ER)-negative subtypes. To identify additional genetic variants for ER-negative breast cancer, we conducted the largest meta-analysis of ER-negative disease to date, comprising 4754 ER-negative cases and 31 663 controls from three GWAS: NCI Breast and Prostate Cancer Cohort Consortium (BPC3) (2188 ER-negative cases; 25 519 controls of European ancestry), Triple Negative Breast Cancer Consortium (TNBCC) (1562 triple negative cases; 3399 controls of European ancestry) and African American Breast Cancer Consortium (AABC) (1004 ER-negative cases; 2745 controls). We performed in silico replication of 86 SNPs at P ≤ 1 × 10(-5) in an additional 11 209 breast cancer cases (946 with ER-negative disease) and 16 057 controls of Japanese, Latino and European ancestry. We identified two novel loci for breast cancer at 20q11 and 6q14. SNP rs2284378 at 20q11 was associated with ER-negative breast cancer (combined two-stage OR = 1.16; P = 1.1 × 10(-8)) but showed a weaker association with overall breast cancer (OR = 1.08, P = 1.3 × 10(-6)) based on 17 869 cases and 43 745 controls and no association with ER-positive disease (OR = 1.01, P = 0.67) based on 9965 cases and 22 902 controls. Similarly, rs17530068 at 6q14 was associated with breast cancer (OR = 1.12; P = 1.1 × 10(-9)), and with both ER-positive (OR = 1.09; P = 1.5 × 10(-5)) and ER-negative (OR = 1.16, P = 2.5 × 10(-7)) disease. We also confirmed three known loci associated with ER-negative (19p13) and both ER-negative and ER-positive breast cancer (6q25 and 12p11). Our results highlight the value of large-scale collaborative studies to identify novel breast cancer risk loci.
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- 2012
43. Circulating prolactin concentrations and risk of type 2 diabetes in US women
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Li, Jun, Rice, Megan S., Huang, Tianyi, Hankinson, Susan E., Clevenger, Charles V., Hu, Frank B., and Tworoger, Shelley S.
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- 2018
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44. Pathway analysis of genome-wide association study data highlights pancreatic development genes as susceptibility factors for pancreatic cancer.
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Li, Donghui, Duell, Eric J, Yu, Kai, Risch, Harvey A, Olson, Sara H, Kooperberg, Charles, Wolpin, Brian M, Jiao, Li, Dong, Xiaoqun, Wheeler, Bill, Arslan, Alan A, Bueno-de-Mesquita, H Bas, Fuchs, Charles S, Gallinger, Steven, Gross, Myron, Hartge, Patricia, Hoover, Robert N, Holly, Elizabeth A, Jacobs, Eric J, Klein, Alison P, LaCroix, Andrea, Mandelson, Margaret T, Petersen, Gloria, Zheng, Wei, Agalliu, Ilir, Albanes, Demetrius, Boutron-Ruault, Marie-Christine, Bracci, Paige M, Buring, Julie E, Canzian, Federico, Chang, Kenneth, Chanock, Stephen J, Cotterchio, Michelle, Gaziano, J Michael, Giovannucci, Edward L, Goggins, Michael, Hallmans, Göran, Hankinson, Susan E, Hoffman Bolton, Judith A, Hunter, David J, Hutchinson, Amy, Jacobs, Kevin B, Jenab, Mazda, Khaw, Kay-Tee, Kraft, Peter, Krogh, Vittorio, Kurtz, Robert C, McWilliams, Robert R, Mendelsohn, Julie B, Patel, Alpa V, Rabe, Kari G, Riboli, Elio, Shu, Xiao-Ou, Tjønneland, Anne, Tobias, Geoffrey S, Trichopoulos, Dimitrios, Virtamo, Jarmo, Visvanathan, Kala, Watters, Joanne, Yu, Herbert, Zeleniuch-Jacquotte, Anne, Amundadottir, Laufey, and Stolzenberg-Solomon, Rachael Z
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Humans ,Pancreatic Neoplasms ,Genetic Predisposition to Disease ,Case-Control Studies ,Polymorphism ,Single Nucleotide ,Genome-Wide Association Study ,Polymorphism ,Single Nucleotide ,Oncology & Carcinogenesis ,Oncology and Carcinogenesis - Abstract
Four loci have been associated with pancreatic cancer through genome-wide association studies (GWAS). Pathway-based analysis of GWAS data is a complementary approach to identify groups of genes or biological pathways enriched with disease-associated single-nucleotide polymorphisms (SNPs) whose individual effect sizes may be too small to be detected by standard single-locus methods. We used the adaptive rank truncated product method in a pathway-based analysis of GWAS data from 3851 pancreatic cancer cases and 3934 control participants pooled from 12 cohort studies and 8 case-control studies (PanScan). We compiled 23 biological pathways hypothesized to be relevant to pancreatic cancer and observed a nominal association between pancreatic cancer and five pathways (P < 0.05), i.e. pancreatic development, Helicobacter pylori lacto/neolacto, hedgehog, Th1/Th2 immune response and apoptosis (P = 2.0 × 10(-6), 1.6 × 10(-5), 0.0019, 0.019 and 0.023, respectively). After excluding previously identified genes from the original GWAS in three pathways (NR5A2, ABO and SHH), the pancreatic development pathway remained significant (P = 8.3 × 10(-5)), whereas the others did not. The most significant genes (P < 0.01) in the five pathways were NR5A2, HNF1A, HNF4G and PDX1 for pancreatic development; ABO for H.pylori lacto/neolacto; SHH for hedgehog; TGFBR2 and CCL18 for Th1/Th2 immune response and MAPK8 and BCL2L11 for apoptosis. Our results provide a link between inherited variation in genes important for pancreatic development and cancer and show that pathway-based approaches to analysis of GWAS data can yield important insights into the collective role of genetic risk variants in cancer.
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- 2012
45. A Genome-Wide Association Meta-Analysis of Circulating Sex Hormone–Binding Globulin Reveals Multiple Loci Implicated in Sex Steroid Hormone Regulation
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Coviello, Andrea D, Haring, Robin, Wellons, Melissa, Vaidya, Dhananjay, Lehtimäki, Terho, Keildson, Sarah, Lunetta, Kathryn L, He, Chunyan, Fornage, Myriam, Lagou, Vasiliki, Mangino, Massimo, Onland-Moret, N Charlotte, Chen, Brian, Eriksson, Joel, Garcia, Melissa, Liu, Yong Mei, Koster, Annemarie, Lohman, Kurt, Lyytikäinen, Leo-Pekka, Petersen, Ann-Kristin, Prescott, Jennifer, Stolk, Lisette, Vandenput, Liesbeth, Wood, Andrew R, Zhuang, Wei Vivian, Ruokonen, Aimo, Hartikainen, Anna-Liisa, Pouta, Anneli, Bandinelli, Stefania, Biffar, Reiner, Brabant, Georg, Cox, David G, Chen, Yuhui, Cummings, Steven, Ferrucci, Luigi, Gunter, Marc J, Hankinson, Susan E, Martikainen, Hannu, Hofman, Albert, Homuth, Georg, Illig, Thomas, Jansson, John-Olov, Johnson, Andrew D, Karasik, David, Karlsson, Magnus, Kettunen, Johannes, Kiel, Douglas P, Kraft, Peter, Liu, Jingmin, Ljunggren, Östen, Lorentzon, Mattias, Maggio, Marcello, Markus, Marcello RP, Mellström, Dan, Miljkovic, Iva, Mirel, Daniel, Nelson, Sarah, Papunen, Laure Morin, Peeters, Petra HM, Prokopenko, Inga, Raffel, Leslie, Reincke, Martin, Reiner, Alex P, Rexrode, Kathryn, Rivadeneira, Fernando, Schwartz, Stephen M, Siscovick, David, Soranzo, Nicole, Stöckl, Doris, Tworoger, Shelley, Uitterlinden, André G, van Gils, Carla H, Vasan, Ramachandran S, Wichmann, H-Erich, Zhai, Guangju, Bhasin, Shalender, Bidlingmaier, Martin, Chanock, Stephen J, De Vivo, Immaculata, Harris, Tamara B, Hunter, David J, Kähönen, Mika, Liu, Simin, Ouyang, Pamela, Spector, Tim D, van der Schouw, Yvonne T, Viikari, Jorma, Wallaschofski, Henri, McCarthy, Mark I, Frayling, Timothy M, Murray, Anna, Franks, Steve, Järvelin, Marjo-Riitta, de Jong, Frank H, Raitakari, Olli, Teumer, Alexander, Ohlsson, Claes, Murabito, Joanne M, and Perry, John RB
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Biological Sciences ,Genetics ,Breast Cancer ,Aging ,Estrogen ,Cancer Genomics ,Urologic Diseases ,Cancer ,Prostate Cancer ,Human Genome ,Women's Health ,Aetiology ,2.1 Biological and endogenous factors ,Metabolic and endocrine ,Alleles ,Female ,Genetic Heterogeneity ,Genome-Wide Association Study ,Gonadal Steroid Hormones ,Humans ,Male ,Metabolic Networks and Pathways ,Polymorphism ,Single Nucleotide ,Sex Characteristics ,Sex Hormone-Binding Globulin ,Developmental Biology - Abstract
Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8 × 10(-106)), PRMT6 (rs17496332, 1p13.3, p = 1.4 × 10(-11)), GCKR (rs780093, 2p23.3, p = 2.2 × 10(-16)), ZBTB10 (rs440837, 8q21.13, p = 3.4 × 10(-09)), JMJD1C (rs7910927, 10q21.3, p = 6.1 × 10(-35)), SLCO1B1 (rs4149056, 12p12.1, p = 1.9 × 10(-08)), NR2F2 (rs8023580, 15q26.2, p = 8.3 × 10(-12)), ZNF652 (rs2411984, 17q21.32, p = 3.5 × 10(-14)), TDGF3 (rs1573036, Xq22.3, p = 4.1 × 10(-14)), LHCGR (rs10454142, 2p16.3, p = 1.3 × 10(-07)), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7 × 10(-08)), and UGT2B15 (rs293428, 4q13.2, p = 5.5 × 10(-06)). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5 × 10(-08), women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ~15.6% and ~8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.
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- 2012
46. Variant ABO Blood Group Alleles, Secretor Status, and Risk of Pancreatic Cancer: Results from the Pancreatic Cancer Cohort Consortium
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Wolpin, Brian M, Kraft, Peter, Xu, Mousheng, Steplowski, Emily, Olsson, Martin L, Arslan, Alan A, Bueno-de-Mesquita, H Bas, Gross, Myron, Helzlsouer, Kathy, Jacobs, Eric J, LaCroix, Andrea, Petersen, Gloria, Stolzenberg-Solomon, Rachael Z, Zheng, Wei, Albanes, Demetrius, Allen, Naomi E, Amundadottir, Laufey, Austin, Melissa A, Boutron-Ruault, Marie-Christine, Buring, Julie E, Canzian, Federico, Chanock, Stephen J, Gaziano, J Michael, Giovannucci, Edward L, Hallmans, Göran, Hankinson, Susan E, Hoover, Robert N, Hunter, David J, Hutchinson, Amy, Jacobs, Kevin B, Kooperberg, Charles, Mendelsohn, Julie B, Michaud, Dominique S, Overvad, Kim, Patel, Alpa V, Sanchéz, Maria-José, Sansbury, Leah, Shu, Xiao-Ou, Slimani, Nadia, Tobias, Geoffrey S, Trichopoulos, Dimitrios, Vineis, Paolo, Visvanathan, Kala, Virtamo, Jarmo, Wactawski-Wende, Jean, Watters, Joanne, Yu, Kai, Zeleniuch-Jacquotte, Anne, Hartge, Patricia, and Fuchs, Charles S
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Digestive Diseases ,Cancer ,Clinical Research ,Genetics ,Rare Diseases ,Pancreatic Cancer ,Prevention ,Human Genome ,Aetiology ,2.1 Biological and endogenous factors ,ABO Blood-Group System ,Alleles ,Cohort Studies ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Genotype ,Glycosyltransferases ,Humans ,Odds Ratio ,Pancreatic Neoplasms ,Phenotype ,Polymorphism ,Single Nucleotide ,Medical and Health Sciences ,Epidemiology - Abstract
BackgroundSubjects with non-O ABO blood group alleles have increased risk of pancreatic cancer. Glycosyltransferase activity is greater for the A(1) versus A(2) variant, whereas O01 and O02 variants are nonfunctioning. We hypothesized: 1) A(1) allele would confer greater risk than A(2) allele, 2) protective effect of the O allele would be equivalent for O01 and O02 variants, 3) secretor phenotype would modify the association with risk.MethodsWe determined ABO variants and secretor phenotype from single nucleotide polymorphisms in ABO and FUT2 genes in 1,533 cases and 1,582 controls from 12 prospective cohort studies. Adjusted odds ratios (OR) for pancreatic cancer were calculated using logistic regression.ResultsAn increased risk was observed in participants with A(1) but not A(2) alleles. Compared with subjects with genotype O/O, genotypes A(2)/O, A(2)/A(1), A(1)/O, and A(1)/A(1) had ORs of 0.96 (95% CI, 0.72-1.26), 1.46 (95% CI, 0.98-2.17), 1.48 (95% CI, 1.23-1.78), and 1.71 (95% CI, 1.18-2.47). Risk was similar for O01 and O02 variant O alleles. Compared with O01/O01, the ORs for each additional allele of O02, A(1), and A(2) were 1.00 (95% CI, 0.87-1.14), 1.38 (95% CI, 1.20-1.58), and 0.96 (95% CI, 0.77-1.20); P, O01 versus O02 = 0.94, A(1) versus A(2) = 0.004. Secretor phenotype was not an effect modifier (P-interaction = 0.63).ConclusionsAmong participants in a large prospective cohort consortium, ABO allele subtypes corresponding to increased glycosyltransferase activity were associated with increased pancreatic cancer risk.ImpactThese data support the hypothesis that ABO glycosyltransferase activity influences pancreatic cancer risk rather than actions of other nearby genes on chromosome 9q34.
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- 2010
47. Family history of cancer and risk of pancreatic cancer: a pooled analysis from the Pancreatic Cancer Cohort Consortium (PanScan).
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Jacobs, Eric J, Chanock, Stephen J, Fuchs, Charles S, Lacroix, Andrea, McWilliams, Robert R, Steplowski, Emily, Stolzenberg-Solomon, Rachael Z, Arslan, Alan A, Bueno-de-Mesquita, H Bas, Gross, Myron, Helzlsouer, Kathy, Petersen, Gloria, Zheng, Wei, Agalliu, Ilir, Allen, Naomi E, Amundadottir, Laufey, Boutron-Ruault, Marie-Christine, Buring, Julie E, Canzian, Federico, Clipp, Sandra, Dorronsoro, Miren, Gaziano, J Michael, Giovannucci, Edward L, Hankinson, Susan E, Hartge, Patricia, Hoover, Robert N, Hunter, David J, Jacobs, Kevin B, Jenab, Mazda, Kraft, Peter, Kooperberg, Charles, Lynch, Shannon M, Sund, Malin, Mendelsohn, Julie B, Mouw, Tracy, Newton, Christina C, Overvad, Kim, Palli, Domenico, Peeters, Petra HM, Rajkovic, Aleksandar, Shu, Xiao-Ou, Thomas, Gilles, Tobias, Geoffrey S, Trichopoulos, Dimitrios, Virtamo, Jarmo, Wactawski-Wende, Jean, Wolpin, Brian M, Yu, Kai, and Zeleniuch-Jacquotte, Anne
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Humans ,Pancreatic Neoplasms ,Genetic Predisposition to Disease ,Case-Control Studies ,Cohort Studies ,Genome-Wide Association Study ,Colo-Rectal Cancer ,Clinical Research ,Rare Diseases ,Aging ,Cancer ,Digestive Diseases ,Prostate Cancer ,Ovarian Cancer ,Pancreatic Cancer ,Breast Cancer ,Prevention ,Urologic Diseases ,2.1 Biological and endogenous factors ,Oncology & Carcinogenesis ,Oncology and Carcinogenesis - Abstract
A family history of pancreatic cancer has consistently been associated with increased risk of pancreatic cancer. However, uncertainty remains about the strength of this association. Results from previous studies suggest a family history of select cancers (i.e., ovarian, breast and colorectal) could also be associated, although not as strongly, with increased risk of pancreatic cancer. We examined the association between a family history of 5 types of cancer (pancreas, prostate, ovarian, breast and colorectal) and risk of pancreatic cancer using data from a collaborative nested case-control study conducted by the Pancreatic Cancer Cohort Consortium. Cases and controls were from cohort studies from the United States, Europe and China, and a case-control study from the Mayo Clinic. Analyses of family history of pancreatic cancer included 1,183 cases and 1,205 controls. A family history of pancreatic cancer in a parent, sibling or child was associated with increased risk of pancreatic cancer [multivariate-adjusted odds ratios (ORs) = 1.76, 95% confidence interval (CI) = 1.19-2.61]. A family history of prostate cancer was also associated with increased risk (OR = 1.45, 95% CI = 1.12-1.89). There were no statistically significant associations with a family history of ovarian cancer (OR = 0.82, 95% CI = 0.52-1.31), breast cancer (OR = 1.21, 95% CI = 0.97-1.51) or colorectal cancer (OR = 1.17, 95% CI = 0.93-1.47). Our results confirm a moderate sized association between a family history of pancreatic cancer and risk of pancreatic cancer and also provide evidence for an association with a family history of prostate cancer worth further study.
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- 2010
48. Evaluation of Candidate Stromal Epithelial Cross-Talk Genes Identifies Association between Risk of Serous Ovarian Cancer and TERT, a Cancer Susceptibility �Hot-Spot�
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Johnatty, Sharon E, Beesley, Jonathan, Chen, Xiaoqing, Macgregor, Stuart, Duffy, David L, Spurdle, Amanda B, deFazio, Anna, Gava, Natalie, Webb, Penelope M, Rossing, Mary Anne, Doherty, Jennifer Anne, Goodman, Marc T, Lurie, Galina, Thompson, Pamela J, Wilkens, Lynne R, Ness, Roberta B, Moysich, Kirsten B, Chang-Claude, Jenny, Wang-Gohrke, Shan, Cramer, Daniel W, Terry, Kathryn L, Hankinson, Susan E, Tworoger, Shelley S, Garcia-Closas, Montserrat, Yang, Hannah, Lissowska, Jolanta, Chanock, Stephen J, Pharoah, Paul D, Song, Honglin, Whitemore, Alice S, Pearce, Celeste L, Stram, Daniel O, Wu, Anna H, Pike, Malcolm C, Gayther, Simon A, Ramus, Susan J, Menon, Usha, Gentry-Maharaj, Aleksandra, Anton-Culver, Hoda, Ziogas, Argyrios, Hogdall, Estrid, Kjaer, Susanne K, Hogdall, Claus, Berchuck, Andrew, Schildkraut, Joellen M, Iversen, Edwin S, Moorman, Patricia G, Phelan, Catherine M, Sellers, Thomas A, Cunningham, Julie M, Vierkant, Robert A, Rider, David N, Goode, Ellen L, Haviv, Izhak, Chenevix-Trench, Georgia, Dermitzakis, Emmanouil T, and Ovarian Cancer Association Consortium", .
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genome-wide association ,single-nucleotide polymorphisms ,incessant ovulation ,colorectal-cancer ,expression ,consortium ,variants ,prostate ,locus ,myc - Abstract
We hypothesized that variants in genes expressed as a consequence of interactions between ovarian cancer cells and the host micro-environment could contribute to cancer susceptibility. We therefore used a two-stage approach to evaluate common single nucleotide polymorphisms (SNPs) in 173 genes involved in stromal epithelial interactions in the Ovarian Cancer Association Consortium (OCAC). In the discovery stage, cases with epithelial ovarian cancer (n = 675) and controls (n = 1,162) were genotyped at 1,536 SNPs using an Illumina GoldenGate assay. Based on Positive Predictive Value estimates, three SNPs-PODXL rs1013368, ITGA6 rs13027811, and MMP3 rs522616-were selected for replication using TaqMan genotyping in up to 3,059 serous invasive cases and 8,905 controls from 16 OCAC case-control studies. An additional 18 SNPs with P(per-allele)= 0.5). However genotypes at TERT rs7726159 were associated with ovarian cancer risk in the smaller, five-study replication study (P(per-allele)=0.03). Combined analysis of the discovery and replication sets for this TERT SNP showed an increased risk of serous ovarian cancer among non-Hispanic whites [adj. OR(per-allele) 1.14 (1.04-1.24) p = 0.003]. Our study adds to the growing evidence that, like the 8q24 locus, the telomerase reverse transcriptase locus at 5p15.33, is a general cancer susceptibility locus.
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- 2010
49. Anthropometric Measures, Body Mass Index, and Pancreatic Cancer: A Pooled Analysis From the Pancreatic Cancer Cohort Consortium (PanScan)
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Arslan, Alan A, Helzlsouer, Kathy J, Kooperberg, Charles, Shu, Xiao-Ou, Steplowski, Emily, Bueno-de-Mesquita, H Bas, Fuchs, Charles S, Gross, Myron D, Jacobs, Eric J, Lacroix, Andrea Z, Petersen, Gloria M, Stolzenberg-Solomon, Rachael Z, Zheng, Wei, Albanes, Demetrius, Amundadottir, Laufey, Bamlet, William R, Barricarte, Aurelio, Bingham, Sheila A, Boeing, Heiner, Boutron-Ruault, Marie-Christine, Buring, Julie E, Chanock, Stephen J, Clipp, Sandra, Gaziano, J Michael, Giovannucci, Edward L, Hankinson, Susan E, Hartge, Patricia, Hoover, Robert N, Hunter, David J, Hutchinson, Amy, Jacobs, Kevin B, Kraft, Peter, Lynch, Shannon M, Manjer, Jonas, Manson, Joann E, McTiernan, Anne, McWilliams, Robert R, Mendelsohn, Julie B, Michaud, Dominique S, Palli, Domenico, Rohan, Thomas E, Slimani, Nadia, Thomas, Gilles, Tjønneland, Anne, Tobias, Geoffrey S, Trichopoulos, Dimitrios, Virtamo, Jarmo, Wolpin, Brian M, Yu, Kai, Zeleniuch-Jacquotte, Anne, and Patel, Alpa V
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Obesity ,Cancer ,Clinical Research ,Nutrition ,Prevention ,Pancreatic Cancer ,Rare Diseases ,Digestive Diseases ,Adult ,Aged ,Aged ,80 and over ,Body Mass Index ,Case-Control Studies ,Female ,Humans ,Logistic Models ,Male ,Middle Aged ,Overweight ,Pancreatic Neoplasms ,Risk Factors ,Sex Distribution ,United States ,Waist Circumference ,Pancreatic Cancer Cohort Consortium ,Clinical Sciences ,Opthalmology and Optometry ,Public Health and Health Services - Abstract
BackgroundObesity has been proposed as a risk factor for pancreatic cancer.MethodsPooled data were analyzed from the National Cancer Institute Pancreatic Cancer Cohort Consortium (PanScan) to study the association between prediagnostic anthropometric measures and risk of pancreatic cancer. PanScan applied a nested case-control study design and included 2170 cases and 2209 control subjects. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using unconditional logistic regression for cohort-specific quartiles of body mass index (BMI [calculated as weight in kilograms divided by height in meters squared]), weight, height, waist circumference, and waist to hip ratio as well as conventional BMI categories (underweight, or = 35.0). Models were adjusted for potential confounders.ResultsIn all of the participants, a positive association between increasing BMI and risk of pancreatic cancer was observed (adjusted OR for the highest vs lowest BMI quartile, 1.33; 95% CI, 1.12-1.58; P(trend) < .001). In men, the adjusted OR for pancreatic cancer for the highest vs lowest quartile of BMI was 1.33 (95% CI, 1.04-1.69; P(trend) < .03), and in women it was 1.34 (95% CI, 1.05-1.70; P(trend) = .01). Increased waist to hip ratio was associated with increased risk of pancreatic cancer in women (adjusted OR for the highest vs lowest quartile, 1.87; 95% CI, 1.31-2.69; P(trend) = .003) but less so in men.ConclusionsThese findings provide strong support for a positive association between BMI and pancreatic cancer risk. In addition, centralized fat distribution may increase pancreatic cancer risk, especially in women.
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- 2010
50. A genome-wide association study identifies pancreatic cancer susceptibility loci on chromosomes 13q22.1, 1q32.1 and 5p15.33.
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Petersen, Gloria M, Amundadottir, Laufey, Fuchs, Charles S, Kraft, Peter, Stolzenberg-Solomon, Rachael Z, Jacobs, Kevin B, Arslan, Alan A, Bueno-de-Mesquita, H Bas, Gallinger, Steven, Gross, Myron, Helzlsouer, Kathy, Holly, Elizabeth A, Jacobs, Eric J, Klein, Alison P, LaCroix, Andrea, Li, Donghui, Mandelson, Margaret T, Olson, Sara H, Risch, Harvey A, Zheng, Wei, Albanes, Demetrius, Bamlet, William R, Berg, Christine D, Boutron-Ruault, Marie-Christine, Buring, Julie E, Bracci, Paige M, Canzian, Federico, Clipp, Sandra, Cotterchio, Michelle, de Andrade, Mariza, Duell, Eric J, Gaziano, J Michael, Giovannucci, Edward L, Goggins, Michael, Hallmans, Göran, Hankinson, Susan E, Hassan, Manal, Howard, Barbara, Hunter, David J, Hutchinson, Amy, Jenab, Mazda, Kaaks, Rudolf, Kooperberg, Charles, Krogh, Vittorio, Kurtz, Robert C, Lynch, Shannon M, McWilliams, Robert R, Mendelsohn, Julie B, Michaud, Dominique S, Parikh, Hemang, Patel, Alpa V, Peeters, Petra HM, Rajkovic, Aleksandar, Riboli, Elio, Rodriguez, Laudina, Seminara, Daniela, Shu, Xiao-Ou, Thomas, Gilles, Tjønneland, Anne, Tobias, Geoffrey S, Trichopoulos, Dimitrios, Van Den Eeden, Stephen K, Virtamo, Jarmo, Wactawski-Wende, Jean, Wang, Zhaoming, Wolpin, Brian M, Yu, Herbert, Yu, Kai, Zeleniuch-Jacquotte, Anne, Fraumeni, Joseph F, Hoover, Robert N, Hartge, Patricia, and Chanock, Stephen J
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Chromosomes ,Human ,Pair 1 ,Chromosomes ,Human ,Pair 5 ,Chromosomes ,Human ,Pair 13 ,Humans ,Carcinoma ,Pancreatic Neoplasms ,Genetic Predisposition to Disease ,Case-Control Studies ,Cohort Studies ,Linkage Disequilibrium ,Polymorphism ,Single Nucleotide ,Genome-Wide Association Study ,Genetic Loci ,Rare Diseases ,Cancer ,Genetics ,Clinical Research ,Pancreatic Cancer ,Digestive Diseases ,Human Genome ,Biological Sciences ,Medical and Health Sciences ,Developmental Biology - Abstract
We conducted a genome-wide association study of pancreatic cancer in 3,851 affected individuals (cases) and 3,934 unaffected controls drawn from 12 prospective cohort studies and 8 case-control studies. Based on a logistic regression model for genotype trend effect that was adjusted for study, age, sex, self-described ancestry and five principal components, we identified eight SNPs that map to three loci on chromosomes 13q22.1, 1q32.1 and 5p15.33. Two correlated SNPs, rs9543325 (P = 3.27 x 10(-11), per-allele odds ratio (OR) 1.26, 95% CI 1.18-1.35) and rs9564966 (P = 5.86 x 10(-8), per-allele OR 1.21, 95% CI 1.13-1.30), map to a nongenic region on chromosome 13q22.1. Five SNPs on 1q32.1 map to NR5A2, and the strongest signal was at rs3790844 (P = 2.45 x 10(-10), per-allele OR 0.77, 95% CI 0.71-0.84). A single SNP, rs401681 (P = 3.66 x 10(-7), per-allele OR 1.19, 95% CI 1.11-1.27), maps to the CLPTM1L-TERT locus on 5p15.33, which is associated with multiple cancers. Our study has identified common susceptibility loci for pancreatic cancer that warrant follow-up studies.
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- 2010
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