Becker, JoelBurik, Casper A. P.Goldman, GrantWang, NancyJayashankar, HariharanBennett, MichaelBelsky, Daniel W.Karlsson Linnér, RichardAhlskog, RafaelKleinman, AaronHinds, David A.Agee, MichelleAlipanahi, BabakAuton, AdamBell, Robert K.Bryc, KatarzynaElson, Sarah L.Fontanillas, PierreFurlotte, Nicholas A.Huber, Karen E.Litterman, Nadia K.McCreight, Jennifer C.McIntyre, Matthew H.Mountain, Joanna L.Northover, Carrie A. M.Pitts, Steven J.Sathirapongsasuti, J. FahSazonova, Olga V.Shelton, Janie F.Shringarpure, SuyashTian, ChaoTung, Joyce Y.Vacic, VladimirWilson, Catherine H.Caspi, AvshalomCorcoran, David L.Moffitt, Terrie E.Poulton, RichieSugden, KarenWilliams, Benjamin S.Harris, Kathleen MullanSteptoe, AndrewAjnakina, OlesyaMilani, LiliEsko, TõnuIacono, William G.McGue, MattMagnusson, Patrik K. E.Mallard, Travis T.Harden, K. PaigeTucker-Drob, Elliot M.Herd, PamelaFreese, JeremyYoung, AlexanderBeauchamp, Jonathan P.Koellinger, Philipp D.Oskarsson, SvenJohannesson, MagnusVisscher, Peter M.Meyer, Michelle N.Laibson, DavidCesarini, DavidBenjamin, Daniel J.Turley, PatrickOkbay, Aysu2023-08-162021-06-17Becker, Joel, Casper A. P. Burik, Grant Goldman, Nancy Wang, Hariharan Jayashankar, Michael Bennett, Daniel W. Belsky et al. "Resource profile and user guide of the Polygenic Index Repository." Nat Hum Behav 5, no. 12 (2021): 1744-1758. DOI: 10.1038/s41562-021-01119-32397-3374https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37376817Here is a complete list of authors: Joel Becker , Casper A.P. Burik , Grant Goldman , Nancy Wang , Hariharan Jayashankar , Michael Bennett , Daniel W. Belsky , Richard Karlsson Linnér , Rafael Ahlskog , Aaron Kleinman , David A. Hinds , 23andMe Research Group , Avshalom Caspi , David L. Corcoran , Terrie E. Moffitt , Richie Poulton , Karen Sugden , Benjamin S. Williams , Kathleen Mullan Harris , Andrew Steptoe , Olesya Ajnakina , Lili Milani , Tõnu Esko , William G. Iacono , Matt McGue , Patrik K.E. Magnusson , Travis T. Mallard , K. Paige Harden , Elliot M. Tucker-Drob , Pamela Herd , Jeremy Freese , Alexander Young , Jonathan P. Beauchamp , Philipp Koellinger , Sven Oskarsson6 , Magnus Johannesson , Peter M. Visscher , Michelle N. Meyer , David Laibson , David Cesarini , Daniel J. Benjamin , Patrick Turley , and Aysu OkbayPolygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is rapidly growing. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs’ prediction accuracies, we constructed them using genome-wide association studies—some not previously published—from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the “additive SNP factor.” Regressions in which the true regressor is the additive SNP factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available.en-USBehavioral NeuroscienceExperimental and Cognitive PsychologySocial PsychologyJournal Article2023-08-1610.1038/s41562-021-01119-3