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1. Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations

Author

Tian Ge, Marguerite R. Irvin, Amit Patki, Vinodh Srinivasasainagendra, Yen-Feng Lin, Hemant K. Tiwari, Nicole D. Armstrong, Barbara Benoit, Chia-Yen Chen, Karmel W. Choi, James J. Cimino, Brittney H. Davis, Ozan Dikilitas, Bethany Etheridge, Yen-Chen Anne Feng, Vivian Gainer, Hailiang Huang, Gail P. Jarvik, Christopher Kachulis, Eimear E. Kenny, Atlas Khan, Krzysztof Kiryluk, Leah Kottyan, Iftikhar J. Kullo, Christoph Lange, Niall Lennon, Aaron Leong, Edyta Malolepsza, Ayme D. Miles, Shawn Murphy, Bahram Namjou, Renuka Narayan, Mark J. O’Connor, Jennifer A. Pacheco, Emma Perez, Laura J. Rasmussen-Torvik, Elisabeth A. Rosenthal, Daniel Schaid, Maria Stamou, Miriam S. Udler, Wei-Qi Wei, Scott T. Weiss, Maggie C. Y. Ng, Jordan W. Smoller, Matthew S. Lebo, James B. Meigs, Nita A. Limdi, and Elizabeth W. Karlson

Subjects
Polygenic risk score, Type 2 diabetes, Diverse populations, Clinical implementation, Medicine, Genetics, QH426-470
Abstract

Abstract Background Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations. Methods We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts. Results The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5–4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance. Conclusions By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.

Published
2022
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2. Fine-mapping the HOXB region detects common variants tagging a rare coding allele: evidence for synthetic association in prostate cancer.

Author

Edward J Saunders, Tokhir Dadaev, Daniel A Leongamornlert, Sarah Jugurnauth-Little, Malgorzata Tymrakiewicz, Fredrik Wiklund, Ali Amin Al Olama, Sara Benlloch, David E Neal, Freddie C Hamdy, Jenny L Donovan, Graham G Giles, Gianluca Severi, Henrik Gronberg, Markus Aly, Christopher A Haiman, Fredrick Schumacher, Brian E Henderson, Sara Lindstrom, Peter Kraft, David J Hunter, Susan Gapstur, Stephen Chanock, Sonja I Berndt, Demetrius Albanes, Gerald Andriole, Johanna Schleutker, Maren Weischer, Børge G Nordestgaard, Federico Canzian, Daniele Campa, Elio Riboli, Tim J Key, Ruth C Travis, Sue A Ingles, Esther M John, Richard B Hayes, Paul Pharoah, Kay-Tee Khaw, Janet L Stanford, Elaine A Ostrander, Lisa B Signorello, Stephen N Thibodeau, Daniel Schaid, Christiane Maier, Adam S Kibel, Cezary Cybulski, Lisa Cannon-Albright, Hermann Brenner, Jong Y Park, Radka Kaneva, Jyotsna Batra, Judith A Clements, Manuel R Teixeira, Jianfeng Xu, Christos Mikropoulos, Chee Goh, Koveela Govindasami, Michelle Guy, Rosemary A Wilkinson, Emma J Sawyer, Angela Morgan, COGS-CRUK GWAS-ELLIPSE (Part of GAME-ON) Initiative, UK Genetic Prostate Cancer Study Collaborators, UK ProtecT Study Collaborators, PRACTICAL Consortium, Douglas F Easton, Ken Muir, Rosalind A Eeles, and Zsofia Kote-Jarai

Subjects
Genetics, QH426-470
Abstract

The HOXB13 gene has been implicated in prostate cancer (PrCa) susceptibility. We performed a high resolution fine-mapping analysis to comprehensively evaluate the association between common genetic variation across the HOXB genetic locus at 17q21 and PrCa risk. This involved genotyping 700 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of 3195 SNPs in 20,440 PrCa cases and 21,469 controls in The PRACTICAL consortium. We identified a cluster of highly correlated common variants situated within or closely upstream of HOXB13 that were significantly associated with PrCa risk, described by rs117576373 (OR 1.30, P = 2.62×10(-14)). Additional genotyping, conditional regression and haplotype analyses indicated that the newly identified common variants tag a rare, partially correlated coding variant in the HOXB13 gene (G84E, rs138213197), which has been identified recently as a moderate penetrance PrCa susceptibility allele. The potential for GWAS associations detected through common SNPs to be driven by rare causal variants with higher relative risks has long been proposed; however, to our knowledge this is the first experimental evidence for this phenomenon of synthetic association contributing to cancer susceptibility.

Published
2014
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3. Data from Gemcitabine and Cytosine Arabinoside Cytotoxicity: Association with Lymphoblastoid Cell Expression

Author

Liewei Wang, Daniel Schaid, Matthew Ames, Michelle Hildebrandt, Stephanie Safgren, Anthony Batzler, Gregory Jenkins, Krishna Kalari, Brooke Fridley, and Liang Li

Abstract

Two cytidine analogues, gemcitabine (dFdC) and 1-β-d-arabinofuranosylcytosine (AraC), show significant therapeutic effect in a variety of cancers. However, response to these drugs varies widely. Evidence from tumor biopsy samples shows that expression levels for genes involved in the cytidine transport, metabolism, and bioactivation pathway contribute to this variation in response. In the present study, we set out to test the hypothesis that variation in gene expression both within and outside of this “pathway” might influence sensitivity to gemcitabine and AraC. Specifically, Affymetrix U133 Plus 2.0 GeneChip and cytotoxicity assays were performed to obtain basal mRNA expression and IC50 values for both drugs in 197 ethnically defined Human Variation Panel lymphoblastoid cell lines. Genes with a high degree of association with IC50 values were involved mainly in cell death, cancer, cell cycle, and nucleic acid metabolism pathways. We validated selected significant genes by performing real-time quantitative reverse transcription-PCR and selected two representative candidates, NT5C3 (within the pathway) and FKBP5 (outside of the pathway), for functional validation. Those studies showed that down-regulation of NT5C3 and FKBP5 altered tumor cell sensitivity to both drugs. Our results suggest that cell-based model system studies, when combined with complementary functional characterization, may help to identify biomarkers for response to chemotherapy with these cytidine analogues. [Cancer Res 2008;68(17):7050–8]

Published
2023

5. Data from Breast Cancer Risk Reduction and Membrane-Bound Catechol O-Methyltransferase Genetic Polymorphisms

Author

Richard Weinshilboum, Daniel Schaid, Shan Wang-Gohrke, Jenny Chang-Claude, Thomas Brüning, Yon Ko, Ute Hamann, Christina Justenhoven, Michel Eichelbaum, Hiltrud Brauch, J. Michael Dixon, William Miller, Thomas Sellers, Zachary Fredericksen, James Ingle, Liewei Wang, Michelle Hildebrandt, Jianping Zhang, Janet Olson, and Yuan Ji

Abstract

Catechol O-methyltransferase (COMT)-catalyzed methylation of catecholestrogens has been proposed to play a protective role in estrogen-induced genotoxic carcinogenesis. We have taken a comprehensive approach to test the hypothesis that genetic variation in COMT might influence breast cancer risk. Fifteen COMT single nucleotide polymorphisms (SNPs) selected on the basis of in-depth resequencing of the COMT gene were genotyped in 1,482 DNA samples from a Mayo Clinic breast cancer case control study. Two common SNPs in the distal promoter for membrane-bound (MB) COMT, rs2020917 and rs737865, were associated with breast cancer risk reduction in premenopausal women in the Mayo Clinic study, with allele-specific odds ratios (OR) of 0.70 [95% confidence interval (CI), 0.52–0.95] and 0.68 (95% CI, 0.51–0.92), respectively. These two SNPs were then subjected to functional genomic analysis and were genotyped in an additional 3,683 DNA samples from two independent case control studies (GENICA and GESBC). Functional genomic experiments showed that these SNPs could up-regulate transcription and that they altered DNA-protein binding patterns. Furthermore, substrate kinetic and exon array analyses suggested a role for MB-COMT in catecholestrogen inactivation. The GENICA results were similar to the Mayo case control observations, with ORs of 0.85 (95% CI, 0.72–1.00) and 0.85 (95% CI, 0.72–1.01) for the two SNPs. No significant effect was observed in the GESBC study. These studies showed that two SNPs in the COMT distal promoter were associated with breast cancer risk reduction in two of three case control studies, compatible with the results of functional genomic experiments, suggesting a role for MB-COMT in breast cancer risk. [Cancer Res 2008;68(14):5997–6005]

Published
2023

6. Supplementary Table 2 from Breast Cancer Risk Reduction and Membrane-Bound Catechol O-Methyltransferase Genetic Polymorphisms

Author

Richard Weinshilboum, Daniel Schaid, Shan Wang-Gohrke, Jenny Chang-Claude, Thomas Brüning, Yon Ko, Ute Hamann, Christina Justenhoven, Michel Eichelbaum, Hiltrud Brauch, J. Michael Dixon, William Miller, Thomas Sellers, Zachary Fredericksen, James Ingle, Liewei Wang, Michelle Hildebrandt, Jianping Zhang, Janet Olson, and Yuan Ji

Abstract

Supplementary Table 2 from Breast Cancer Risk Reduction and Membrane-Bound Catechol O-Methyltransferase Genetic Polymorphisms

Published
2023

7. Supplementary Table 3 from Breast Cancer Risk Reduction and Membrane-Bound Catechol O-Methyltransferase Genetic Polymorphisms

Author

Richard Weinshilboum, Daniel Schaid, Shan Wang-Gohrke, Jenny Chang-Claude, Thomas Brüning, Yon Ko, Ute Hamann, Christina Justenhoven, Michel Eichelbaum, Hiltrud Brauch, J. Michael Dixon, William Miller, Thomas Sellers, Zachary Fredericksen, James Ingle, Liewei Wang, Michelle Hildebrandt, Jianping Zhang, Janet Olson, and Yuan Ji

Abstract

Supplementary Table 3 from Breast Cancer Risk Reduction and Membrane-Bound Catechol O-Methyltransferase Genetic Polymorphisms

Published
2023

9. Supplementary Table 1 from Breast Cancer Risk Reduction and Membrane-Bound Catechol O-Methyltransferase Genetic Polymorphisms

Author

Richard Weinshilboum, Daniel Schaid, Shan Wang-Gohrke, Jenny Chang-Claude, Thomas Brüning, Yon Ko, Ute Hamann, Christina Justenhoven, Michel Eichelbaum, Hiltrud Brauch, J. Michael Dixon, William Miller, Thomas Sellers, Zachary Fredericksen, James Ingle, Liewei Wang, Michelle Hildebrandt, Jianping Zhang, Janet Olson, and Yuan Ji

Abstract

Supplementary Table 1 from Breast Cancer Risk Reduction and Membrane-Bound Catechol O-Methyltransferase Genetic Polymorphisms

Published
2023

10. Quantifying factors that affect polygenic risk score performance across diverse ancestries and age groups for body mass index

Author

Daniel Hui, Brenda Xiao, Ozan Dikilitas, Robert R. Freimuth, Marguerite R. Irvin, Gail P. Jarvik, Leah Kottyan, Iftikhar Kullo, Nita A. Limdi, Cong Liu, Yuan Luo, Bahram Namjou, Megan J. Puckelwartz, Daniel Schaid, Hemant Tiwari, Wei-Qi Wei, Shefali Verma, Dokyoon Kim, and Marylyn D. Ritchie

Abstract

Polygenic risk scores (PRS) have led to enthusiasm for precision medicine. However, it is well documented that PRS do not generalize across groups differing in ancestry or sample characteristics e.g., age. Quantifying performance of PRS across different groups of study participants, using genome-wide association study (GWAS) summary statistics from multiple ancestry groups and sample sizes, and using different linkage disequilibrium (LD) reference panels may clarify which factors are limiting PRS transferability. To evaluate these factors in the PRS generation process, we generated body mass index (BMI) PRS (PRSBMI) in the Electronic Medical Records and Genomics (eMERGE) network (N=75,661). Analyses were conducted in two ancestry groups (European and African) and three age ranges (adult, teenagers, and children). For PRSBMI calculations, we evaluated five LD reference panels and three sets of GWAS summary statistics of varying sample size and ancestry. PRSBMI performance increased for both African and European ancestry individuals using cross-ancestry GWAS summary statistics compared to European-only summary statistics (6.3% and 3.7% relative R2 increase, respectively, pAfrican=0.038, pEuropean=6.26x10-4). The effects of LD reference panels were more pronounced in African ancestry study datasets. PRSBMI performance degraded in children; R2 was less than half of teenagers or adults. The effect of GWAS summary statistics sample size was small when modeled with the other factors. Additionally, the potential of using a PRS generated for one trait to predict risk for comorbid diseases is not well understood especially in the context of cross-ancestry analyses - we explored clinical comorbidities from the electronic health record associated with PRSBMI and identified significant associations with type 2 diabetes and coronary atherosclerosis. In summary, this study quantifies the effects that ancestry, GWAS summary statistic sample size, and LD reference panel have on PRS performance, especially in cross-ancestry and age-specific analyses.

Published
2022

11. Returning integrated genomic risk and clinical recommendations: the eMERGE study

Author

Jodell E. Linder, Aimee Allworth, Sarah T. Bland, Pedro J. Caraballo, Rex L. Chisholm, Ellen Wright Clayton, David R. Crosslin, Ozan Dikilitas, Alanna DiVietro, Edward D. Esplin, Sophie Forman, Robert R. Freimuth, Adam S. Gordon, Richard Green, Maegan V. Harden, Ingrid A. Holm, Gail P. Jarvik, Elizabeth W. Karlson, Sofia Labrecque, Niall J. Lennon, Nita A. Limdi, Kathleen F. Mittendorf, Shawn N. Murphy, Lori Orlando, Cynthia A. Prows, Luke V. Rasmussen, Laura Rasmussen-Torvik, Robb Rowley, Konrad Teodor Sawicki, Tara Schmidlen, Shannon Terek, David Veenstra, Digna R. Velez Edwards, Devin Absher, Noura S. Abul-Husn, Jorge Alsip, Hana Bangash, Mark Beasley, Jennifer E. Below, Eta S. Berner, James Booth, Wendy K. Chung, James J. Cimino, John Connolly, Patrick Davis, Beth Devine, Stephanie M. Fullerton, Candace Guiducci, Melissa L. Habrat, Heather Hain, Hakon Hakonarson, Margaret Harr, Eden Haverfield, Valentina Hernandez, Christin Hoell, Martha Horike-Pyne, George Hripcsak, Marguerite R. Irvin, Christopher Kachulis, Dean Karavite, Eimear E. Kenny, Atlas Khan, Krzysztof Kiryluk, Bruce Korf, Leah Kottyan, Iftikhar J. Kullo, Katie Larkin, Cong Liu, Edyta Malolepsza, Teri A. Manolio, Thomas May, Elizabeth M. McNally, Frank Mentch, Alexandra Miller, Sean D. Mooney, Priyanka Murali, Brenda Mutai, Naveen Muthu, Bahram Namjou, Emma F. Perez, Megan J. Puckelwartz, Tejinder Rakhra-Burris, Dan M. Roden, Elisabeth A. Rosenthal, Seyedmohammad Saadatagah, Maya Sabatello, Dan J. Schaid, Baergen Schultz, Lynn Seabolt, Gabriel Q. Shaibi, Richard R. Sharp, Brian Shirts, Maureen E. Smith, Jordan W. Smoller, Rene Sterling, Sabrina A. Suckiel, Jeritt Thayer, Hemant K. Tiwari, Susan B. Trinidad, Theresa Walunas, Wei-Qi Wei, Quinn S. Wells, Chunhua Weng, Georgia L. Wiesner, Ken Wiley, Josh F. Peterson, Adam Gordon, Agboade Sobowale, Akshar Patel, Alanna Strong, Alborz Sherafati, Alborz Sherfati, Alex Bick, Alka Chandel, Alyssa Rosenthal, Amit Khera, Amy Kontorovich, Andrew Beck, Andy Beck, Angelica Espinoza, Anna Lewis, Anya Prince, Ayuko Iverson, Bahram Namjou Khales, Barbara Benoit, Becca Hernan, Ben Kallman, Ben Kerman, Ben Shoemaker, Benjamin Satterfield, Bethany Etheridge, Blake Goff, Bob Freimuth, Bob Grundmeier, Brenae Collier, Brett Harnett, Brian Chang, Brian Piening, Brittney Davis, Candace Patterson, Carmen Demetriou, Casey Ta, Catherine Hammack, Catrina Nelson, Caytie Gascoigne, Chad Dorn, Chad Moretz, Chris Kachulis, Christie Hoell, Christine Cowles, Christoph Lange, Cindy Prows, Cole Brokamp, Courtney Scherr, Crystal Gonzalez, Cynthia Ramirez, Daichi Shimbo, Dan Roden, Daniel Schaid, Dave Kaufman, David Crosslin, David Kochan, Davinder Singh, Debbie Abrams, Digna Velez Edwards, Eduardo Morales, Edward Esplin, Ehsan Alipour, Eimear Kenny, Elisabeth Rosenthal, Eliza Duvall, Elizabeth McNally, Elizabeth Bhoj, Elizabeth Cohn, Elizabeth Hibler, Elizabeth Karlson, Ellen Clayton, Emily Chesnut, Emily DeFranco, Emily Gallagher, Emily Soper, Emma Perez, Erin Cash, Eta Berner, Fei Wang, Firas Wehbe, Francisco Ricci, Gabriel Shaibi, Gail Jarvik, George Hahn, Georgia Wiesner, Gillian Belbin, Gio Davogustto, Girish Nadkarni, Haijun Qiu, Hannah Beasley, Hao Liu, Heide Aungst, Hemant Tiwari, Hillary Duckham, Hope Thomas, Iftikhar Kullo, Ingrid Holm, Isabelle Allen, Iuliana Ionita-Laza, Jacklyn Hellwege, Jacob Petrzelka, Jacqueline Odgis, Jahnavi Narula, Jake Petrzelka, Jalpa Patel, James Cimino, James Meigs, James Snyder, Janet Olson, Janet Zahner, Jeff Pennington, Jen Pacheco, Jennifer Allen Pacheco, Jennifer Morse, Jeremy Corsmo, Jim Cimino, Jingheng Chen, Jocelyn Fournier, Jodell Jackson, Joe Glessner, Joel Pacyna, Johanna Smith, John Lynch, John Shelley, Jonathan Mosley, Jordan Nestor, Jordan Smoller, Joseph Kannry, Joseph Sutton, Josh Peterson, Joshua Smith, Julia Galasso, Julia Smith, Julia Wynn, Justin Gundelach, Justin Starren, Karmel Choi, Kate Mittendorf, Katherine Anderson, Katherine Bonini, Kathleen Leppig, Kathleen Muenzen, Kelsey Stuttgen, Kenny Nguyen, Kevin Dufendach, Kiley Atkins, Konrad Sawicki, Kristjan Norland, Laura Beskow, Li Hsu, Lifeng Tian, Lisa Mahanta, Lisa Martin, Lisa Wang, Lizbeth Gomez, Lorenzo Thompson, Lucas Richter, Luke Rasmussen, Lynn Petukhova, Madison O’Brien, Maegan Harden, Malia Fullerton, Marta Guindo, Martha Horike, Marwah Abdalla, Marwan Hamed, Mary Beth Terry, Mary Maradik, Matt Wyatt, Matthew Davis, Matthew Lebo, Maureen Smith, Maya del Rosario, Meckenzie Behr, Meg Roy-Puckelwartz, Mel Habrat, Melanie Myers, Meliha Yetisgen, Merve Iris, Michael DaSilva, Michael Preuss, Michelle McGowan, Mingjian Shi, Minoli Perera, Minta Thomas, Mitch Elkind, Mohammad Abbass, Mohammad Saadatagah, Molly Hess, Molly Maradik, Nataraja 'RJ' Vaitinadin, Nataraja Vaitinadin, Neil Netherly, Niall Lennon, Ning Shang, Nita Limdi, Noah Forrest, Noheli Romero, Nora Robinson, Noura Abul-Husn, Omar Elsekaily, Patricia Kovatch, Paul Appelbaum, Paul Francaviglia, Paul O’Reilly, Paulette Chandler, Pedro Caraballo, Peter Tarczy-Hornoch, Pierre Shum, Priya Marathe, Qiping Feng, Quinn Wells, Rachel Atchley, Radhika Narla, Rene Barton, Rex Chisholm, Richard Sharp, Riki Peters, Rita Kukafka, Robert Freimuth, Robert Green, Robert Winter, Roger Mueller, Ruth Loos, Ryan Irvin, Sabrina Suckiel, Sajjad Hussain, Samer Sharba, Sandy Aronson, Sarah Jones, Sarah Knerr, Scott Nigbur, Scott Weiss, Sean Mooney, Sharon Aufox, Sharon Nirenberg, Shawn Murphy, Sheila O’Byrne, Shing Wang (Sam) Choi, Sienna Aguilar, S.T. Bland, Stefanie Rodrigues, Stephanie Ledbetter, Stephanie Rutledge, Stuart James Booth, Su Xian, Susan Brown Trinidad, Suzanne Bakken, Teri Manolio, Tesfaye Mersha, Thevaa Chandereng, Tian Ge, Todd Edwards, Tom Kaszemacher, Valerie Willis, Vemi Desai, Vimi Desai, Virginia Lorenzi, Vivian Gainer, Wendy Chung, Wu-Chen Su, Xiao Chang, Yiqing Zhao, Yuan Luo, and Yufeng Shen

Subjects
Genetics (clinical)
Abstract

Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk.To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores (PRS), monogenic risks, family history, and clinical risk assessments via a Genome Informed Risk Assessment (GIRA) report and will assess uptake of care recommendations after return of results.GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022.Return of a novel report for communicating monogenic, polygenic, and family history based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

Published
2022

13. TBX2 is preferentially amplified in BRCA1- and BRCA2-related breast tumors

Author

Colleen S, Sinclair, Camilo, Adem, Ali, Naderi, Cheryl L, Soderberg, Michele, Johnson, Kangjian, Wu, Linda, Wadum, Vicki L, Couch, Thomas A, Sellers, Daniel, Schaid, Jeffrey, Slezak, Zach, Fredericksen, James N, Ingle, Lynn, Hartmann, Robert B, Jenkins, and Fergus J, Couch

Subjects
Adult, Aged, 80 and over, Genes, BRCA2, Gene Amplification, Genes, BRCA1, Breast Neoplasms, Middle Aged, Mutation, Humans, Female, T-Box Domain Proteins, In Situ Hybridization, Fluorescence, Aged, Neoplasm Staging
Abstract

The chromosome 17q23 region is frequently amplified in breast tumors. Gain of the region is present in 50% of BRCA1-associated breast tumors and 87% of BRCA2-associated breast tumors. The amplification frequency of the RPS6KB1 and TBX2 oncogenes from this amplicon was compared in 27 BRCA1 and BRCA2 mutant breast tumors, 15 breast tumors from high-risk patients with no BRCA1 or BRCA2 mutations, and 62 matched sporadic breast tumor controls. TBX2 was determined to be preferentially amplified and overexpressed in BRCA1 and BRCA2 mutant tumors, whereas RPS6KB1 was not, suggesting a role for TBX2 amplification in the development of BRCA1- and BRCA2-associated breast tumors.

Published
2002

14. Validation of the reflux symptom questionnaire

Author

Joseph Murray A, Alan Cameron J, Lawrence Burgart J, Yvonne Romero, Cyndy Hardtke L, Giles Locke R, Daniel Schaid J, and Massimo Conio

Subjects
medicine.medical_specialty, Hepatology, business.industry, Internal medicine, Gastroenterology, medicine, Reflux symptom, business, Surgery
Abstract

Purpose: To prospectively validate the Reflux Symptom Questionnaire (RSQ) developed by Locke, et al. (Mayo Clin Proc 1994; 69: 539|[ndash]|547).

Published
2000

15. A comprehensive examination of CYP19 variation and risk of breast cancer using two haplotype-tagging approaches.

Author

Janet Olson, James Ingle, Cynthia Ma, Linda Pelleymounter, Daniel Schaid, V. Pankratz, Robert Vierkant, Zachary Fredericksen, Yanhong Wu, Fergus Couch, Celine Vachon, Thomas Sellers, and Richard Weinshilboum

Subjects
ESTROGEN, CANCER risk factors, BREAST cancer, WOMEN'S health
Abstract

AbstractBackground  Numerous studies point to a positive relationship between elevated levels of estrogens and increased risk of breast. Androgens are converted to estrogens by the aromatase enzyme, which is encoded by the CYP19 gene. We recently published resequencing data on 88 polymorphisms identified in that gene. The hypothesis tested in this study was that polymorphisms, or haplotypes, in CYP19 are related to risk of breast cancer.Methods  Incident cases of breast cancer were identified through the Division of Medical Oncology at the Mayo Clinic in Rochester, MN. Controls were patients visiting Mayo for an annual medical examination. Controls were frequency matched to cases based on age and region of residence. Tag-polymorphisms were selected using 2 methods: (1) 12 variants using the tag-selection method of Carlson et al. (Am J Hum Genet74:106–120, 2004); and (2) 12 variants using the haplotype method of Stram (Genet Epidemiol27:365–374, 2004). Six SNPs were selected by both methods. Genotyping was conducted using SNPStream, TaqMan and RFLP analyses. Logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals (CI). Analyses were conducted among all cases and controls, or stratified by estrogen receptor alpha (ER) status and/or menopausal status.Results  A total of 750 cases (60% postmenopausal) and 732 controls (75% postmenopausal) were included. No association with breast cancer risk was detected for individual variants, selected tagSNPs or hap-tag SNPs despite 80% power to detect OR as low as 1.49 for minor allele frequency (MAF) of 0.10. Similarly, stratified analyses based on ER status or menopausal status failed to detect any association with breast cancer risk.Conclusion  These analyses suggest that variants ofCYP19are not associated with risk of breast cancer. [ABSTRACT FROM AUTHOR]

Published
2007
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