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2. Recommendations for the collection and use of multiplexed functional data for clinical variant interpretation

Author

Hannah Gelman, Jennifer N. Dines, Jonathan Berg, Alice H. Berger, Sarah Brnich, Fuki M. Hisama, Richard G. James, Alan F. Rubin, Jay Shendure, Brian Shirts, Douglas M. Fowler, Lea M. Starita, and On behalf of the Brotman Baty Institute Mutational Scanning Working Group

Subjects
Medicine, Genetics, QH426-470
Abstract

Abstract Variants of uncertain significance represent a massive challenge to medical genetics. Multiplexed functional assays, in which the functional effects of thousands of genomic variants are assessed simultaneously, are increasingly generating data that can be used as additional evidence for or against variant pathogenicity. Such assays have the potential to resolve variants of uncertain significance, thereby increasing the clinical utility of genomic testing. Existing standards from the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) and new guidelines from the Clinical Genome Resource (ClinGen) establish the role of functional data in variant interpretation, but do not address the specific challenges or advantages of using functional data derived from multiplexed assays. Here, we build on these existing guidelines to provide recommendations to experimentalists for the production and reporting of multiplexed functional data and to clinicians for the evaluation and use of such data. By following these recommendations, experimentalists can produce transparent, complete, and well-validated datasets that are primed for clinical uptake. Our recommendations to clinicians and diagnostic labs on how to evaluate the quality of multiplexed functional datasets, and how different datasets could be incorporated into the ACMG/AMP variant-interpretation framework, will hopefully clarify whether and how such data should be used. The recommendations that we provide are designed to enhance the quality and utility of multiplexed functional data, and to promote their judicious use.

Published
2019
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3. Socioeconomic Status and Interest in Genetic Testing in a US-Based Sample

Author

EJ Dusic, Deborah J. Bowen, Robin Bennett, Kevin C. Cain, Tesla Theoryn, Mariebeth Velasquez, Elizabeth Swisher, Jeannine M. Brant, Brian Shirts, and Catharine Wang

Subjects
genetic testing, socioeconomic status, cancer, Medicine
Abstract

Cancer is a significant burden, particularly to individuals of low socioeconomic status (SES). Genetic testing can provide information about an individual’s risk of developing cancer and guide future screening and preventative services. However, there are significant financial barriers, particularly for individuals of low SES. This study used the Early Detection of Genetic Risk (EDGE) Study’s patient baseline survey (n = 2329) to evaluate the relationship between socioeconomic status and interest in pursuing hereditary cancer genetic testing. Analysis was completed for two interest outcomes—overall interest in genetic testing and interest in genetic testing if the test were free or low cost. Many demographic and SES variables were predictors for interest in genetic testing, including education, income, and MacArthur Subjective Social Scale (SSS). After controlling for the healthcare system, age, and gender, having a higher education level and a higher household income were associated with greater general interest. Lower SSS was associated with greater interest in genetic testing if the test was free or low cost. If genetic testing is the future of preventative medicine, more work needs to be performed to make this option accessible to low-SES groups and to ensure that those services are used by the most underserved populations.

Published
2022
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4. Supp. Table S22 from Genetic Mechanisms of Immune Evasion in Colorectal Cancer

Author

Ulrike Peters, Shuji Ogino, Antoni Ribas, Charles S. Fuchs, Thomas J. Hudson, Levi A. Garraway, Eric S. Lander, Stacey B. Gabriel, Jesse M. Zaretsky, Syed H. Zaidi, Ming Yu, Catherine J. Wu, David A. Wheeler, Alexander Upfill-Brown, Jennifer Tsoi, Wei Sun, Janet L. Stanford, Sachet Shukla, Brian Shirts, Eve Shinbrot, Daniel Sanghoon Shin, Stephen J. Salipante, Ben J. Raphael, Elleanor H. Quist, Cristina Puig-Saus, Colin C. Pritchard, Matteo Pellegrini, Brian B. Nadel, Dennis J. Montoya, Mark D.M. Leiserson, Paige Krystofinski, Yeon Joo Kim, Jeroen R. Huyghe, Siwen Hu-Lieskovan, Li Hsu, William M. Grady, Milan S. Geybels, Helena Escuin-Ordinas, Charles Connolly, Gabriel Abril-Rodriguez, Katsuhiko Nosho, Teppei Morikawa, Kentaro Inamura, Zhi Rong Qian, Reiko Nishihara, Jonathan A. Nowak, Michael Quist, Xinmeng Jasmine Mu, Tsuyoshi Hamada, Daniel K. Wells, Marios Giannakis, and Catherine S. Grasso

Abstract

Supplementary Table S22: Segmented b-allele deficits

Published
2023

5. Supp. Tables S16-S19 from Genetic Mechanisms of Immune Evasion in Colorectal Cancer

Author

Ulrike Peters, Shuji Ogino, Antoni Ribas, Charles S. Fuchs, Thomas J. Hudson, Levi A. Garraway, Eric S. Lander, Stacey B. Gabriel, Jesse M. Zaretsky, Syed H. Zaidi, Ming Yu, Catherine J. Wu, David A. Wheeler, Alexander Upfill-Brown, Jennifer Tsoi, Wei Sun, Janet L. Stanford, Sachet Shukla, Brian Shirts, Eve Shinbrot, Daniel Sanghoon Shin, Stephen J. Salipante, Ben J. Raphael, Elleanor H. Quist, Cristina Puig-Saus, Colin C. Pritchard, Matteo Pellegrini, Brian B. Nadel, Dennis J. Montoya, Mark D.M. Leiserson, Paige Krystofinski, Yeon Joo Kim, Jeroen R. Huyghe, Siwen Hu-Lieskovan, Li Hsu, William M. Grady, Milan S. Geybels, Helena Escuin-Ordinas, Charles Connolly, Gabriel Abril-Rodriguez, Katsuhiko Nosho, Teppei Morikawa, Kentaro Inamura, Zhi Rong Qian, Reiko Nishihara, Jonathan A. Nowak, Michael Quist, Xinmeng Jasmine Mu, Tsuyoshi Hamada, Daniel K. Wells, Marios Giannakis, and Catherine S. Grasso

Abstract

Supplementary Tables S16-S19, describing IHC results on NHS/HPFS data

Published
2023

6. Supp. Tables S1, S3-S15, S20, and S23 from Genetic Mechanisms of Immune Evasion in Colorectal Cancer

Author

Ulrike Peters, Shuji Ogino, Antoni Ribas, Charles S. Fuchs, Thomas J. Hudson, Levi A. Garraway, Eric S. Lander, Stacey B. Gabriel, Jesse M. Zaretsky, Syed H. Zaidi, Ming Yu, Catherine J. Wu, David A. Wheeler, Alexander Upfill-Brown, Jennifer Tsoi, Wei Sun, Janet L. Stanford, Sachet Shukla, Brian Shirts, Eve Shinbrot, Daniel Sanghoon Shin, Stephen J. Salipante, Ben J. Raphael, Elleanor H. Quist, Cristina Puig-Saus, Colin C. Pritchard, Matteo Pellegrini, Brian B. Nadel, Dennis J. Montoya, Mark D.M. Leiserson, Paige Krystofinski, Yeon Joo Kim, Jeroen R. Huyghe, Siwen Hu-Lieskovan, Li Hsu, William M. Grady, Milan S. Geybels, Helena Escuin-Ordinas, Charles Connolly, Gabriel Abril-Rodriguez, Katsuhiko Nosho, Teppei Morikawa, Kentaro Inamura, Zhi Rong Qian, Reiko Nishihara, Jonathan A. Nowak, Michael Quist, Xinmeng Jasmine Mu, Tsuyoshi Hamada, Daniel K. Wells, Marios Giannakis, and Catherine S. Grasso

Abstract

Supplementary Tables S1, S3 through S15, S20, and S23

Published
2023

7. Data from Genetic Mechanisms of Immune Evasion in Colorectal Cancer

Author

Ulrike Peters, Shuji Ogino, Antoni Ribas, Charles S. Fuchs, Thomas J. Hudson, Levi A. Garraway, Eric S. Lander, Stacey B. Gabriel, Jesse M. Zaretsky, Syed H. Zaidi, Ming Yu, Catherine J. Wu, David A. Wheeler, Alexander Upfill-Brown, Jennifer Tsoi, Wei Sun, Janet L. Stanford, Sachet Shukla, Brian Shirts, Eve Shinbrot, Daniel Sanghoon Shin, Stephen J. Salipante, Ben J. Raphael, Elleanor H. Quist, Cristina Puig-Saus, Colin C. Pritchard, Matteo Pellegrini, Brian B. Nadel, Dennis J. Montoya, Mark D.M. Leiserson, Paige Krystofinski, Yeon Joo Kim, Jeroen R. Huyghe, Siwen Hu-Lieskovan, Li Hsu, William M. Grady, Milan S. Geybels, Helena Escuin-Ordinas, Charles Connolly, Gabriel Abril-Rodriguez, Katsuhiko Nosho, Teppei Morikawa, Kentaro Inamura, Zhi Rong Qian, Reiko Nishihara, Jonathan A. Nowak, Michael Quist, Xinmeng Jasmine Mu, Tsuyoshi Hamada, Daniel K. Wells, Marios Giannakis, and Catherine S. Grasso

Abstract

To understand the genetic drivers of immune recognition and evasion in colorectal cancer, we analyzed 1,211 colorectal cancer primary tumor samples, including 179 classified as microsatellite instability–high (MSI-high). This set includes The Cancer Genome Atlas colorectal cancer cohort of 592 samples, completed and analyzed here. MSI-high, a hypermutated, immunogenic subtype of colorectal cancer, had a high rate of significantly mutated genes in important immune-modulating pathways and in the antigen presentation machinery, including biallelic losses of B2M and HLA genes due to copy-number alterations and copy-neutral loss of heterozygosity. WNT/β-catenin signaling genes were significantly mutated in all colorectal cancer subtypes, and activated WNT/β-catenin signaling was correlated with the absence of T-cell infiltration. This large-scale genomic analysis of colorectal cancer demonstrates that MSI-high cases frequently undergo an immunoediting process that provides them with genetic events allowing immune escape despite high mutational load and frequent lymphocytic infiltration and, furthermore, that colorectal cancer tumors have genetic and methylation events associated with activated WNT signaling and T-cell exclusion.Significance: This multi-omic analysis of 1,211 colorectal cancer primary tumors reveals that it should be possible to better monitor resistance in the 15% of cases that respond to immune blockade therapy and also to use WNT signaling inhibitors to reverse immune exclusion in the 85% of cases that currently do not. Cancer Discov; 8(6); 730–49. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 663

Published
2023

8. 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

9. Modeling the impact of data sharing on variant classification

Author

James Casaletto, Melissa Cline, and Brian Shirts

Subjects
Health Informatics
Abstract

ObjectiveMany genetic variants are classified, but many more are variants of uncertain significance (VUS). Clinical observations of patients and their families may provide sufficient evidence to classify VUS. Understanding how long it takes to accumulate sufficient patient data to classify VUS can inform decisions in data sharing, disease management, and functional assay development.Materials and MethodsOur software models the accumulation of clinical evidence (and excludes all other types of evidence) to measure their unique impact on variant interpretation. We illustrate the time and probability for VUS classification when laboratories share evidence, when they silo evidence, and when they share only variant interpretations.ResultsUsing conservative assumptions for frequencies of observed clinical evidence, our models show the probability of classifying rare pathogenic variants with an allele frequency of 1/100 000 increases from less than 25% with no data sharing to nearly 80% after one year when labs share data, with nearly 100% classification after 5 years. Conversely, our models found that extremely rare (1/1 000 000) variants have a low probability of classification using only clinical data.DiscussionThese results quantify the utility of data sharing and demonstrate the importance of alternative lines of evidence for interpreting rare variants. Understanding variant classification circumstances and timelines provides valuable insight for data owners, patients, and service providers. While our modeling parameters are based on our own assumptions of the rate of accumulation of clinical observations, users may download the software and run simulations with updated parameters.ConclusionsThe modeling software is available at https://github.com/BRCAChallenge/classification-timelines.

Published
2022

10. Quantifying the impact of data sharing on variant classification

Author

James Casaletto, Melissa Cline, and Brian Shirts

Abstract

Many genomic variants are currently classified, but many more are extremely rare, have minimal associated patient data, and are classified as variants uncertain significance (VUS). Accumulating patient data such as family history and de novo status can help classify variants. Understanding potential timelines for data accumulation and variant classification can inform reporting, diagnosis, and treatment decisions. We modeled future clinical data observations with different strategies for sharing and aggregating clinical evidence for variants across multiple sequencing centers over time. Models illustrate how long it takes for variants to be classified when evidence is or is not shared between clinical laboratories and compared to when only variant interpretations are shared. When sequencing centers share evidence the probability of classifying a one in 100,000 pathogenic variant increases from less than 25% to nearly 80% after one year and to nearly 100% with 5 years of observations. Extremely rare variants have a low likelihood of classification using clinical data even with optimal data sharing. Sharing clinical evidence between laboratories will lead to faster and more certain classifications. Modeling can effectively illustrate the likelihood of variant classification under current classification frameworks and may help define realistic provider and patient expectations.

Published
2021

15. Rare loss of function variants in candidate genes and risk of colorectal cancer

Author

Benjamin Voight, David Jacobs, Fridtjof Thomas, Sandosh Padmanabhan, Kamakshi Lakshminarayan, James Pankow, Adam Gordon, Christie Ballantyne, Carlos D. Bustamante, Kathryn Lunetta, Brian Shirts, Aaron Quinlan, Michael Konstan, Margaret Rosenfeld, John Carr, John Hardy, Matthew Budoff, Sudha Seshadri, Aaron Chidekel, Bette Caan, William M Gershan, Stephen Rich, John P. Ioannidis, Pamela Schreiner, Robert Wise, and Joshua Akey

Subjects
0301 basic medicine, Oncology, Adult, Male, Candidate gene, medicine.medical_specialty, Adolescent, Colorectal cancer, Biology, Article, 03 medical and health sciences, Deoxyribonuclease (Pyrimidine Dimer), Risk Factors, Internal medicine, Genotype, Genetic variation, Genetics, medicine, Humans, neoplasms, Genetics (clinical), Genetic testing, Aged, Aged, 80 and over, BRCA2 Protein, medicine.diagnostic_test, BRIP1, Family aggregation, Genetic Variation, Middle Aged, medicine.disease, digestive system diseases, Fanconi Anemia Complementation Group Proteins, 030104 developmental biology, Genetic Loci, Cohort, Female, Colorectal Neoplasms, RNA Helicases
Abstract

PURPOSE: Although ~25% of colorectal cancer or polyps (CRC/P) cases show familial aggregation, current germline genetic testing identifies a causal genotype in the 16 major genes associated with high penetrance CRC/P in only 20% of these cases. As there are likely other genes underlying heritable CRC/P, we evaluated the association of variation at novel loci with CRC/P. METHODS: We evaluated 158 a priori selected candidate genes by comparing the number of rare potentially disruptive variants (PDVs) found in 84 CRC/P cases without an identified CRC/P risk associated variant and 2440 controls. We repeated this analysis using an additional 73 CRC/P cases. We also compared the frequency of PDVs in select genes among CRC/P cases with two publicly available data sets. RESULTS: We found a significant enrichment of PDVs in cases versus controls: 20% of cases vs. 11.5% of controls with ≥ 1 PDV (OR=1.9, p=0.01) in the original set of cases. Among the second cohort of CRC/P cases, 18% had a PDV, significantly different from 11.5% (p=0.02). Logistic regression, adjusting for ancestry and multiple testing, indicated association between CRC/P and PDVs in NTHL1 (p=0.0001), BRCA2 (p=0.01) and BRIP1 (p=0.04). However, there was no significant difference in the frequency of PDVs at each of these genes between all 157 CRC/P cases and two publicly available data sets. CONCLUSION: These results suggest an increased presence of PDVs in CRC/P cases and support further investigation of the association of NTHL1, BRCA2 and BRIP1 variation with CRC/P.

Published
2018

16. Clinical Sequencing Exploratory Research Consortium: Accelerating Evidence-Based Practice of Genomic Medicine

Author

Robert C. Green, Katrina A.B. Goddard, Gail P. Jarvik, Laura M. Amendola, Paul S. Appelbaum, Jonathan S. Berg, Barbara A. Bernhardt, Leslie G. Biesecker, Sawona Biswas, Carrie L. Blout, Kevin M. Bowling, Kyle B. Brothers, Wylie Burke, Charlisse F. Caga-anan, Arul M. Chinnaiyan, Wendy K. Chung, Ellen W. Clayton, Gregory M. Cooper, Kelly East, James P. Evans, Stephanie M. Fullerton, Levi A. Garraway, Jeremy R. Garrett, Stacy W. Gray, Gail E. Henderson, Lucia A. Hindorff, Ingrid A. Holm, Michelle Huckaby Lewis, Carolyn M. Hutter, Pasi A. Janne, Steven Joffe, David Kaufman, Bartha M. Knoppers, Barbara A. Koenig, Ian D. Krantz, Teri A. Manolio, Laurence McCullough, Jean McEwen, Amy McGuire, Donna Muzny, Richard M. Myers, Deborah A. Nickerson, Jeffrey Ou, Donald W. Parsons, Gloria M. Petersen, Sharon E. Plon, Heidi L. Rehm, J. Scott Roberts, Dan Robinson, Joseph S. Salama, Sarah Scollon, Richard R. Sharp, Brian Shirts, Nancy B. Spinner, Holly K. Tabor, Peter Tarczy-Hornoch, David L. Veenstra, Nikhil Wagle, Karen Weck, Benjamin S. Wilfond, Kirk Wilhelmsen, Susan M. Wolf, Julia Wynn, Joon-Ho Yu, Michelle Amaral, Laura Amendola, Samuel J. Aronson, Shubhangi Arora, Danielle R. Azzariti, Greg S. Barsh, E.M. Bebin, Barbara B. Biesecker, Brian L. Brown, Amber A. Burt, Peter H. Byers, Muge G. Calikoglu, Sara J. Carlson, Nizar Chahin, Kurt D. Christensen, Wendy Chung, Allison L. Cirino, Ellen Clayton, Laura K. Conlin, Greg M. Cooper, David R. Crosslin, James V. Davis, Kelly Davis, Matthew A. Deardorff, Batsal Devkota, Raymond De Vries, Pamela Diamond, Michael O. Dorschner, Noreen P. Dugan, Dmitry Dukhovny, Matthew C. Dulik, Kelly M. East, Edgar A. Rivera-Munoz, Barbara Evans, Jessica Everett, Nicole Exe, Zheng Fan, Lindsay Z. Feuerman, Kelly Filipski, Candice R. Finnila, Kristen Fishler, Bob Ghrundmeier, Karen Giles, Marian J. Gilmore, Zahra S. Girnary, Katrina Goddard, Steven Gonsalves, Adam S. Gordon, Michele C. Gornick, William M. Grady, David E. Gray, Robert Green, Robert S. Greenwood, Amanda M. Gutierrez, Paul Han, Ragan Hart, Patrick Heagerty, Naomi Hensman, Susan M. Hiatt, Patricia Himes, Fuki M. Hisama, Carolyn Y. Ho, Lily B. Hoffman-Andrews, Celine Hong, Martha J. Horike-Pyne, Sara Hull, Seema Jamal, Brian C. Jensen, Steve Joffe, Jennifer Johnston, Dean Karavite, Tia L. Kauffman, Dave Kaufman, Whitley Kelley, Jerry H. Kim, Christine Kirby, William Klein, Bartha Knoppers, Sek Won Kong, Ian Krantz, Joel B. Krier, Neil E. Lamb, Michele P. Lambert, Lan Q. Le, Matthew S. Lebo, Alexander Lee, Kaitlyn B. Lee, Niall Lennon, Michael C. Leo, Kathleen A. Leppig, Katie Lewis, Michelle Lewis, Neal I. Lindeman, Nicole Lockhart, Bob Lonigro, Edward J. Lose, Philip J. Lupo, Laura Lyman Rodriguez, Frances Lynch, Kalotina Machini, Calum MacRae, Daniel S. Marchuk, Josue N. Martinez, Aaron Masino, Heather M. McLaughlin, Carmit McMullen, Piotr A. Mieczkowski, Jeff Miller, Victoria A. Miller, Rajen Mody, Sean D. Mooney, Elizabeth G. Moore, Elissa Morris, Michael Murray, David Ng, Nelly M. Oliver, Will Parsons, Donald L. Patrick, Jeffrey Pennington, Denise L. Perry, Gloria Petersen, Sharon Plon, Katie Porter, Bradford C. Powell, Sumit Punj, Carmen Radecki Breitkopf, Robin A. Raesz-Martinez, Wendy H. Raskind, Dean A. Reigar, Jacob A. Reiss, Carla A. Rich, Carolyn Sue Richards, Christine Rini, Scott Roberts, Peggy D. Robertson, Jill O. Robinson, Marguerite E. Robinson, Myra I. Roche, Edward J. Romasko, Elisabeth A. Rosenthal, Joseph Salama, Maria I. Scarano, Jennifer Schneider, Christine E. Seidman, Bryce A. Seifert, Brian H. Shirts, Lynette M. Sholl, Javed Siddiqui, Elian Silverman, Shirley Simmons, Janae V. Simons, Debra Skinner, Elena Stoffel, Natasha T. Strande, Shamil Sunyaev, Virginia P. Sybert, Jennifer Taber, Deanne M. Taylor, Christian R. Tilley, Ashley Tomlinson, Susan Trinidad, Ellen Tsai, Peter Ubel, Eliezer M. Van Allen, Jason L. Vassy, Pankaj Vats, Victoria L. Vetter, Raymond D. Vries, Sarah A. Walser, Rebecca C. Walsh, Allison Werner-Lin, Jana Whittle, Ben Wilfond, Kirk C. Wilhelmsen, Yaping Yang, Carol Young, and Brian J. Zikmund-Fisher

Subjects
0301 basic medicine, Adult, Evidence-based practice, Biomedical Research, Best practice, Exploratory research, MEDLINE, Genomics, Computational biology, 030105 genetics & heredity, Bioinformatics, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Population Groups, Genetics, Medicine, Genomic medicine, Humans, Genetics(clinical), Exome, Child, Genetics (clinical), Exome sequencing, Medical education, Clinical Trials as Topic, business.industry, Genome, Human, Correction, High-Throughput Nucleotide Sequencing, Human genetics, United States, 3. Good health, National Human Genome Research Institute (U.S.), 030104 developmental biology, Cardiovascular Diseases, Evidence-Based Practice, Human genome, business, Psychology, Software
Abstract

Despite rapid technical progress and demonstrable effectiveness for some types of diagnosis and therapy, much remains to be learned about clinical genome and exome sequencing (CGES) and its role within the practice of medicine. The Clinical Sequencing Exploratory Research (CSER) consortium includes 18 extramural research projects, one National Human Genome Research Institute (NHGRI) intramural project, and a coordinating center funded by the NHGRI and National Cancer Institute. The consortium is exploring analytic and clinical validity and utility, as well as the ethical, legal, and social implications of sequencing via multidisciplinary approaches; it has thus far recruited 5,577 participants across a spectrum of symptomatic and healthy children and adults by utilizing both germline and cancer sequencing. The CSER consortium is analyzing data and creating publically available procedures and tools related to participant preferences and consent, variant classification, disclosure and management of primary and secondary findings, health outcomes, and integration with electronic health records. Future research directions will refine measures of clinical utility of CGES in both germline and somatic testing, evaluate the use of CGES for screening in healthy individuals, explore the penetrance of pathogenic variants through extensive phenotyping, reduce discordances in public databases of genes and variants, examine social and ethnic disparities in the provision of genomics services, explore regulatory issues, and estimate the value and downstream costs of sequencing. The CSER consortium has established a shared community of research sites by using diverse approaches to pursue the evidence-based development of best practices in genomic medicine.

Published
2016

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