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The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores
Madeline L. Page, Elizabeth Vance, Matthew Cloward, Ed Ringger, Louisa Dayton, Mark Ebbert, Myron Weiner, Paul Aisen, Rebecca A. Petersen, Clifford R. Jack, William J. Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, R. C. Green, Andrew J. Saykin, Julia Morris, Richard J. Perrin, Zaven S. Khachaturian, María C. Carrillo, William Z. Potter, Lisa L. Barnes, Manon Bernard, Héctor M. González, Calvin Wai-Loon Ho, John Hsiao, Jacqueline M Jackson, Eliezer Masliah, D. Masterman, Ozioma C. Okonkwo, Louise Ryan, Jonathan I. Silverberg, D. T. Sacrey, Juliet Fockler, Costanza Conti, Dallas P. Veitch, John Neuhaus, Chongyao Jin, Rachel L. Nosheny, Miriam T. Ashford, Derek Flenniken, Adrieene Kormos, T. Monine, Michael S. Rafii, Rajiv Raman, Gustavo Jiménez, Michael Donohue, Devon Gessert, Joel Salazar, Christina Zimmerman, Yuliana Cabrera, Sarah Walter, Gabrielle Miller, G. Coker, T. Clanton, Lindsey Hergesheimer, Samuel Pattillo Smith, Oluwatoyin Adegoke, P. Mahboubi, Scott D. Moore, J. Pizzola, E. Shaffer, B. Sloan, Danielle Harvey, Arivn Forghanian-Arani, Bret Borowski, Chad Ward, Charlotte Schwarz, David T. Jones, J Günter, Kejal Kantarci, Matthew L. Senjem, Prashanthi Vemuri, Ronald E. Reid, Nick C. Fox, Ian B. Malone, Pamela J. Thompson, Sophia I. Thomopoulos, Talia M. Nir, Neda Jahanshad, Charles DeCarli, Alex Knaack, D. Tosun-Turgut, S. R. Chen, Mi Kyung Choe, Karen Crawford, Paul A. Yushkevich, Sayantan Das, Robert A. Koeppe, Eric M. Reiman, K. Chen, Chester A. Mathis, Susan Landau, N. J. Cairns, Erin Householder, Erin Franklin, Harold S. Bernhardt, L. Taylor-Reinwald, J. Q. Tojanowki, Magdalena Korecka, Michal Figurski, Scott Neu, Kwangsik Nho, Shannon L. Risacher, Liana G. Apostolova, Li Shen, Tatiana Foroud, Kelly Nudelman, Kelley Faber, K. Wilmes, M. W. Winer, L. J. Thal, Lisa C. Silbert, Betty Lind, Rachel Crissey, Jeffrey Kaye, R. Carter, Sara Dolen, Joseph F. Quinn, L. S. Schneider, Sonia Pawluczyk, Mauricio Becerra, Liberty Teodoro, Karen Dagerman, Bryan M. Spann, Jessica V. Brewer, Helen Vanderswag, Jaimie Ziolkowski, Judith L. Heidebrink, Lisa Zbizek-Nulph, Jasmine Lord, Sara S. Mason, Colleen S. Albers, David Knopman, Kris Johnson, Javier Villanueva-Meyer, Valory Pavlik, Nathaniel Pacini, A. E. Lamb, Joseph S. Kass, Rachelle S. Doody, Victoria Shibley, Mahabub Arefin Chowdhury, Susan Rountree, My Ngoc Thi Dang, Yaakov Stern, Lawrence S. Honig, Akiva Mintz, Beau M. Ances, David Winkfield, Maria Carroll, Georgia Stobbs-Cucchi, Karen Oliver, Mary L. Creech, Mark A. Mintun, Stacy Schneider, David Geldmacher, Marissa Natelson Love, Randall Griffith, David W. Clark, John Brockington, Daniel Marson, Hillel Grossman, Martin Goldstein, J. Greenberg, Effie Mitsis, Raj C. Shah, Melissa Lamar, Patricia Samuels, Ranjan Duara, Maria T. Greig‐Custo, Raúl Adrián Huerta Rodríguez, M. S. Albert, Chiadi U. Onyike, Leonie Farrington, Scott Rudow, Rostislav Brichko, Stephanie Kielb, A. David Smith, Balebail Ashok Raj, Kristin Fargher, Martin Sadowski, Thomas Wısnıewskı, Melanie Shulman, Arline Faustin, Jagadeesh S. Rao, Karen M. Castro, Anaztasia Ulysse, S. Chen, Mohammed O. Sheikh, Jamika Singleton-Garvin, P. Murali Doraiswamy, Jeffrey R. Petrella, Olga James, Terence Z. Wong, Salvador Borges‐Neto, Jason Karlawish, David A. Wolk, Sanjeev Vaishnavi, Christopher Clark, Steven E. Arnold, Charles D. Smith, Gregory A. Jicha, Riham El Khouli, Flavius D. Raslau, Oscar L. López, MaryAnn Oakley, D.M. Simpson, Anton P. Porsteinsson, Kathleen Martin, Nancy Kowalski, Melanie Keltz, Bonnie S. Goldstein, Kelly M. Makino, M. Saleem Ismail, Connie Brand, Gaby Thai, Aimee Pierce, Elizabeth Sosa, Megan Witbracht, B. Kelley, Văn Tuân Nguyên, Kyle Womack, Dana Mathews, M. Quiceno, Allan I. Levey, James J. Lah, Ihab Hajjar, Janet S. Cellar, Jane Burns, Russell H. Swerdlow, William M. Brooks, Daniel Silverman, Sarah Kremen, Kathleen Tingus, Po H. Lu, George Bartzokis, Ellen Woo, Eric Teng, N. R. Graff-Radford, Francine Parfitt, Martin R. Farlow, Ann Marie Hake, Brandy R. Matthews, Jared R. Brosch, Scott Herring, C H van Dyck, Adam P. Mecca, Susan P. Good, Martha G. MacAvoy, Robyn Carson, Paroma Varma, Howard Chertkow, Susan Vaitekunis, Chris Hosein, Samantha L. Black, Bojana Stefanovic, Chris Heyn, Ging‐Yuek Robin Hsiung, E. Kim, Benita Mudge, Vesna Sossi, Howard Feldman, Michele Assaly, Elizabeth Finger, Stephen Pasternak, Irina Rachinsky, A. Kertesz, Dick Drost, J. Rogers, Ian Grant, Brittanie Muse, Emily Rogalskı, J. Robson, Marek M. Mesulam, Diana Kerwin, Chong Wu, Nicholas D. Johnson, Kristine Lipowski, Sarah J. Weintraub, Borna Bonakdarpour, Nunzio Pomara, Raymundo Hernando, Antero Sarrael, Howard J. Rosen, Barbara L. Miller, Daniel Perry, Richard Turner, Brigid Reynolds, Kimberly G. Y. McCann, Jessica Poe, Ruth Sperling, Gad A. Marshall, Jerome A. Yesavage, J Taylor, Sheau‐yueh J. Chao, Jonathan R. I. Coleman, Julie D. White, Barton Lane, Allyson Rosen, J. R. Tinklenberg, Christine M. Belden, Alireza Atri, K. A. Clark, Edward Zamrini, Marwan N. Sabbagh, Ronald Killiany, Robert A. Stern, Jesse Mez, Neil W. Kowall, Andrew E. Budson, Thomas O. Obisesan, Oyonumo Ntekim, Saba Wolday, Javed Khan, Evaristus Nwulia, Sheeba Nadarajah, Alan J. Lerner, Paula Ogrocki, Curtis Tatsuoka, Parianne Fatica, Pauline Maillard, John Olichney, Owen Carmichael, Victoria Bates, Horacio Capote, Michelle Rainka, Michael Borrie, T. Lee, Robert Bartha, Spencer D. Johnson, Shailendra Asthana, C. M. Carlson, Arnaud Perrin, A. Burke, Douglas W. Scharre, Maria Kataki, Rawan Tarawneh, De Hart, Earl A. Zimmerman, Dzintra Celmins, Del D. Miller, Laura L. Boles Ponto, K. E. Smith, Hristina Koleva, Hyungsub Shim, Kisung Nam, Susan K. Schultz, Jeff D. Williamson, Suzanne Craft, Jo Cleveland, Melinda A. Yang, Kaycee M. Sink, Brian R. Ott, Jonathan Drake, Geoffrey Tremont, Lori A. Daiello, Aaron Ritter, Charles Bernick, Donna Munic, A. O’Connell, Jacobo Mintzer, Amy L. Williams, Joseph C. Masdeu, Jingchunzi Shi, Alex Pena Garcia, Paul Newhouse, Steven Potkin, Stephen Salloway, P. Malloy, Stephen Correia, Smita Kittur, G. D. Perlson, Karen Blank, Kevin D. Anderson, Laura A. Flashman, Marc Seltzer, Mary L. Hynes, Robert B. Santulli, Norman Relkin, Gloria Chiang, A. Lee, Meng Lin, Lisa Ravdin, Justin Miller, John S. K. Kauwe
Bibliographic record
VenueCommunications Biology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsParkwood InstituteSt Joseph's Health CareSunnybrook Health Science CentreUniversity of British ColumbiaMcGill UniversityJewish General Hospital
FundersNational Institute on AgingUniversity of California, San FranciscoNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health ResearchUniversity of California, Los AngelesGenentechNational Institutes of HealthIXICONational Institute of General Medical SciencesH. Lundbeck A/SServierJewish General HospitalEisaiNorthern California Institute for Research and EducationMcGill UniversityPfizerNorthwestern UniversityBiogenBioClinicaF. Hoffmann-La RocheBrigham Young UniversityUniversity of Southern CaliforniaNovartis Pharmaceuticals CorporationU.S. Department of DefenseBrightFocus FoundationEli Lilly and CompanyBristol-Myers SquibbAlzheimer's AssociationYale UniversityU.S. Department of Health and Human ServicesUniversity of California, IrvineGeorgetown UniversityFoundation for the National Institutes of HealthUniversity of KentuckyEmory UniversityBrigham and Women's HospitalAlzheimer's Disease Neuroimaging InitiativeMedical Research CouncilMeso Scale Diagnostics
KeywordsPolygenic risk scoreBiobankGenome-wide association studyConfoundingComputer scienceCalculatorBioinformaticsMedicineBiologyGeneticsSingle-nucleotide polymorphismInternal medicine
Abstract
The process of identifying suitable genome-wide association (GWA) studies and formatting the data to calculate multiple polygenic risk scores on a single genome can be laborious. Here, we present a centralized polygenic risk score calculator currently containing over 250,000 genetic variant associations from the NHGRI-EBI GWAS Catalog for users to easily calculate sample-specific polygenic risk scores with comparable results to other available tools. Polygenic risk scores are calculated either online through the Polygenic Risk Score Knowledge Base (PRSKB; https://prs.byu.edu ) or via a command-line interface. We report study-specific polygenic risk scores across the UK Biobank, 1000 Genomes, and the Alzheimer's Disease Neuroimaging Initiative (ADNI), contextualize computed scores, and identify potentially confounding genetic risk factors in ADNI. We introduce a streamlined analysis tool and web interface to calculate and contextualize polygenic risk scores across various studies, which we anticipate will facilitate a wider adaptation of polygenic risk scores in future disease research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score0.998
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
Opus teacher head0.038
GPT teacher head0.323
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
Study designObservational
Domainnot available
GenreEmpirical
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".
Quick stats
Citations16
Published2022
Admission routes2
Has abstractyes