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4 results on '"Christopher Kachulis"'

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. 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

3. 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

4. Status and design of two-phase liquid-Xenon compton-imaging detector

Author

Moshe Gai, Sidney Cahn, Blair Edwards, Daniel McKinsey, Christopher G. Wahl, Ethan Bernard, N. A. Larsen, Christopher Kachulis, B. P. Tennyson, and N. Destefano

Subjects
Physics, Scintillation, Physics::Instrumentation and Detectors, business.industry, Detector, chemistry.chemical_element, Noise (electronics), Particle identification, Optics, Xenon, chemistry, Nuclear electronics, Neutron detection, Neutron, business
Abstract

PIXeY (Particle Identification in Xenon at Yale) is an R&D detector that uses xenon in gas-phase, liquid-phase, or two-phase mode. It features drift and proportional electric field regions set with 92%-transparent wire grids, highly reflective Teflon walls, and 14 high-quantum-efficiency PMTs (Hamamatsu R8778) to record both initial scintillation light (S1) and proportional scintillation light (S2) from the drifting of charge in the proportional region. It promises energy resolution and gamma/neutron discrimination that are competitive with previous systems. Recently, PIXeY has run stably for 12 weeks and the first data have been collected. Initial results are presented, along with planned design modifications that will transform PIXeY into a Compton imager. Crossed wires with 3-mm spacing will be used to record interaction locations. A preamp to read out each wire is also being designed to fulfill space and noise constraints. Finally, in order to precisely know the energy from each gamma-ray interaction, the scintillation light from each interaction must be distinguished from that due to others. Simulation is used to determine the optimal optical segmentation of the active volume using thin Teflon walls.

Published
2012

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