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8 results on '"Niall Lennon"'

1. Genetic sex validation for sample tracking in next-generation sequencing clinical testing

Author

Jianhong Hu, Viktoriya Korchina, Hana Zouk, Maegan V. Harden, David Murdock, Alyssa Macbeth, Steven M. Harrison, Niall Lennon, Christie Kovar, Adithya Balasubramanian, Lan Zhang, Gauthami Chandanavelli, Divya Pasham, Robb Rowley, Ken Wiley, Maureen E. Smith, Adam Gordon, Gail P. Jarvik, Patrick Sleiman, Melissa A. Kelly, Harris T. Bland, Mullai Murugan, Eric Venner, Eric Boerwinkle, the eMERGE III consortium, Cynthia Prows, Lisa Mahanta, Heidi L. Rehm, Richard A. Gibbs, and Donna M. Muzny

Subjects
Next-generation sequencing (NGS), Clinical testing, Sex concordance, SNP genotyping, Medicine, Biology (General), QH301-705.5, Science (General), Q1-390
Abstract

Abstract Objective Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups. Results Precise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors (49.09%), samples from transgender participants (3.64%) and stem cell or bone marrow transplant patients (7.27%) along with undetermined sample mix-ups (40%) for which sample swaps occurred prior to arrival at genome centers, however the exact cause of the events at the sampling sites resulting in the mix-ups were not able to be determined.

Published
2024
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2. 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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3. Using synthetic chromosome controls to evaluate the sequencing of difficult regions within the human genome

Author

Andre L. M. Reis, Ira W. Deveson, Bindu Swapna Madala, Ted Wong, Chris Barker, Joshua Xu, Niall Lennon, Weida Tong, Tim R. Mercer, and on behalf of the SEQC2 Consortium

Subjects
Biology (General), QH301-705.5, Genetics, QH426-470
Abstract

Abstract Background Next-generation sequencing (NGS) can identify mutations in the human genome that cause disease and has been widely adopted in clinical diagnosis. However, the human genome contains many polymorphic, low-complexity, and repetitive regions that are difficult to sequence and analyze. Despite their difficulty, these regions include many clinically important sequences that can inform the treatment of human diseases and improve the diagnostic yield of NGS. Results To evaluate the accuracy by which these difficult regions are analyzed with NGS, we built an in silico decoy chromosome, along with corresponding synthetic DNA reference controls, that encode difficult and clinically important human genome regions, including repeats, microsatellites, HLA genes, and immune receptors. These controls provide a known ground-truth reference against which to measure the performance of diverse sequencing technologies, reagents, and bioinformatic tools. Using this approach, we provide a comprehensive evaluation of short- and long-read sequencing instruments, library preparation methods, and software tools and identify the errors and systematic bias that confound our resolution of these remaining difficult regions. Conclusions This study provides an analytical validation of diagnosis using NGS in difficult regions of the human genome and highlights the challenges that remain to resolve these difficult regions.

Published
2022
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4. Pooling for SARS-CoV2 Surveillance: Validation and Strategy for Implementation in K-12 Schools

Author

Alexandra M. Simas, Jimmy W. Crott, Chris Sedore, Augusta Rohrbach, Anthony P. Monaco, Stacey B. Gabriel, Niall Lennon, Brendan Blumenstiel, and Caroline A. Genco

Subjects
pooled testing methodology, COVID-19, SARS-CoV-2, RT-PCR assay, screening, Public aspects of medicine, RA1-1270
Abstract

Repeated testing of a population is critical for limiting the spread of the SARS-CoV-2 virus and for the safe reopening of educational institutions such as kindergarten—grade 12 (K-12) schools and colleges. Many screening efforts utilize the CDC RT-PCR based assay which targets two regions of the novel Coronavirus nucleocapsid gene. The standard approach of testing each person individually, however, poses a financial burden to these institutions and is therefore a barrier to using testing for re-opening. Pooling samples from multiple individuals into a single test is an attractive alternate approach that promises significant cost savings—however the specificity and sensitivity of such approaches needs to be assessed prior to deployment. To this end, we conducted a pilot study to evaluate the feasibility of analyzing samples in pools of eight by the established RT-PCR assay. Participants (1,576) were recruited from amongst the Tufts University community undergoing regular screening. Each volunteer provided two swabs, one analyzed separately and the other in a pool of eight. Because the positivity rate was very low, we spiked approximately half of the pools with laboratory-generated swabs produced from known positive cases outside the Tufts testing program. The results of pooled tests had 100% correspondence with those of their respective individual tests. We conclude that pooling eight samples does not negatively impact the specificity or sensitivity of the RT-PCR assay and suggest that this approach can be utilized by institutions seeking to reduce surveillance costs.

Published
2021
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5. 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

6. Cost-efficient whole genome-sequencing using novel mostly natural sequencing-by-synthesis chemistry and open fluidics platform

Author

Gilad Almogy, Mark Pratt, Florian Oberstrass, Linda Lee, Dan Mazur, Nate Beckett, Omer Barad, Ilya Soifer, Eddie Perelman, Yoav Etzioni, Martin Sosa, April Jung, Tyson Clark, Eliane Trepagnier, Gila Lithwick-Yanai, Sarah Pollock, Gil Hornung, Maya Levy, Matthew Coole, Tom Howd, Megan Shand, Yossi Farjoun, James Emery, Giles Hall, Samuel Lee, Takuto Sato, Ricky Magner, Sophie Low, Andrew Bernier, Bharathi Gandi, Jack Stohlman, Corey Nolet, Siobhan Donovan, Brendan Blumenstiel, Michelle Cipicchio, Sheila Dodge, Eric Banks, Niall Lennon, Stacey Gabriel, and Doron Lipson

Abstract

We introduce a massively parallel novel sequencing platform that combines an open flow cell design on a circular wafer with a large surface area and mostly natural nucleotides that allow optical end-point detection without reversible terminators. This platform enables sequencing billions of reads with longer read length (∼300bp) and fast runs times ( 85%), at a low cost of $1/Gb. We establish system performance by whole-genome sequencing of the Genome-In-A-Bottle reference samples HG001-7, demonstrating high accuracy for SNPs (99.6%) and Indels in homopolymers up to length 10 (96.4%) across the vast majority (>98%) of the defined high-confidence regions of these samples. We demonstrate scalability of the whole-genome sequencing workflow by sequencing an additional 224 selected samples from the 1000 Genomes project achieving high concordance with reference data.

Published
2022

7. Genome-wide polygenic score to predict chronic kidney disease across ancestries

Author

Atlas Khan, Michael C. Turchin, Amit Patki, Vinodh Srinivasasainagendra, Ning Shang, Rajiv Nadukuru, Alana C. Jones, Edyta Malolepsza, Ozan Dikilitas, Iftikhar J. Kullo, Daniel J. Schaid, Elizabeth Karlson, Tian Ge, James B. Meigs, Jordan W. Smoller, Christoph Lange, David R. Crosslin, Gail P. Jarvik, Pavan K. Bhatraju, Jacklyn N. Hellwege, Paulette Chandler, Laura Rasmussen Torvik, Alex Fedotov, Cong Liu, Christopher Kachulis, Niall Lennon, Noura S. Abul-Husn, Judy H. Cho, Iuliana Ionita-Laza, Ali G. Gharavi, Wendy K. Chung, George Hripcsak, Chunhua Weng, Girish Nadkarni, Marguerite R. Irvin, Hemant K. Tiwari, Eimear E. Kenny, Nita A. Limdi, and Krzysztof Kiryluk

Subjects
Multifactorial Inheritance, Genotype, General Medicine, Apolipoprotein L1, Polymorphism, Single Nucleotide, Article, General Biochemistry, Genetics and Molecular Biology, Gene Frequency, Risk Factors, Humans, Genetic Predisposition to Disease, Renal Insufficiency, Chronic, Alleles, Genome-Wide Association Study
Abstract

Chronic kidney disease (CKD) is a common complex condition associated with high morbidity and mortality. Polygenic prediction could enhance CKD screening and prevention; however, this approach has not been optimized for ancestrally diverse populations. By combining APOL1 risk genotypes with genome-wide association studies (GWAS) of kidney function, we designed, optimized and validated a genome-wide polygenic score (GPS) for CKD. The new GPS was tested in 15 independent cohorts, including 3 cohorts of European ancestry (n = 97,050), 6 cohorts of African ancestry (n = 14,544), 4 cohorts of Asian ancestry (n = 8,625) and 2 admixed Latinx cohorts (n = 3,625). We demonstrated score transferability with reproducible performance across all tested cohorts. The top 2% of the GPS was associated with nearly threefold increased risk of CKD across ancestries. In African ancestry cohorts, the APOL1 risk genotype and polygenic component of the GPS had additive effects on the risk of CKD.

Published
2021

8. The All of Us Research Program: Data quality, utility, and diversity

Author

Andrea H. Ramirez, Lina Sulieman, David J. Schlueter, Alese Halvorson, Jun Qian, Francis Ratsimbazafy, Roxana Loperena, Kelsey Mayo, Melissa Basford, Nicole Deflaux, Karthik N. Muthuraman, Karthik Natarajan, Abel Kho, Hua Xu, Consuelo Wilkins, Hoda Anton-Culver, Eric Boerwinkle, Mine Cicek, Cheryl R. Clark, Elizabeth Cohn, Lucila Ohno-Machado, Sheri D. Schully, Brian K. Ahmedani, Maria Argos, Robert M. Cronin, Christopher O’Donnell, Mona Fouad, David B. Goldstein, Philip Greenland, Scott J. Hebbring, Elizabeth W. Karlson, Parinda Khatri, Bruce Korf, Jordan W. Smoller, Stephen Sodeke, John Wilbanks, Justin Hentges, Stephen Mockrin, Christopher Lunt, Stephanie A. Devaney, Kelly Gebo, Joshua C. Denny, Robert J. Carroll, David Glazer, Paul A. Harris, George Hripcsak, Anthony Philippakis, Dan M. Roden, Brian Ahmedani, Christine D. Cole Johnson, Habib Ahsan, Donna Antoine-LaVigne, Glendora Singleton, Eric Topol, Katie Baca-Motes, Steven Steinhubl, James Wade, Mark Begale, Praduman Jain, Scott Sutherland, Beth Lewis, Melissa Behringer, Ali G. Gharavi, Louise Bier, Murray H. Brilliant, Narayana Murali, Scott Joseph Hebbring, Dorothy Farrar-Edwards, Elizabeth Burnside, Marc K. Drezner, Amy Taylor, Veena Channamsetty, Wanda Montalvo, Yashoda Sharma, Carmen Chinea, Nancy Jenks, Steve Thibodeau, Beverly Wilson Holmes, Eric Schlueter, Ever Collier, Joyce Winkler, John Corcoran, Nick D’Addezio, Martha Daviglus, Robert Winn, Dan Roden, Joshua Denny, Kim Doheny, Debbie Nickerson, Evan Eichler, Gail Jarvik, Gretchen Funk, Heidi Rehm, Niall Lennon, Sekar Kathiresan, Stacey Gabriel, Richard Gibbs, Edgar M. Gil Rico, Joannie Grand, Paul Harris, Elizabeth Shenkman, William R. Hogan, Priscilla Igho-Pemu, Cliff Pollan, Milena Jorge, Sally Okun, Jordan Smoller, Shawn N. Murphy, Margaret Elizabeth Ross, Rainu Kaushal, Eboni Winford, Febe Wallace, Vik Kheterpal, Akinlolu Ojo, Francisco A. Moreno, Irving Kron, Rachele Peterson, Usha Menon, Patricia Watkins Lattimore, Noga Leviner, Juno Obedin-Maliver, Mitchell Lunn, Lynda Malik-Gagnon, Lara Mangravite, Adria Marallo, Oscar Marroquin, Shyam Visweswaran, Steven Reis, Gailen Marshall, Patrick McGovern, Deb Mignucci, John Moore, Fatima Munoz, Gregory Talavera, George T. O'Connor, Christopher O'Donnell, Greg Orr, Fornessa Randal, Andreas A. Theodorou, Eric Reiman, Mercedita Roxas-Murray, Louisa Stark, Ronnie Tepp, Alicia Zhou, Scott Topper, Rhonda Trousdale, Phil Tsao, Lisa Weidman, Scott T. Weiss, David Wellis, Jeffrey Whittle, Amanda Wilson, Stephan Zuchner, and Michael E. Zwick

Subjects
General Decision Sciences
Published
2022

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