eprintid: 10131355 rev_number: 22 eprint_status: archive userid: 608 dir: disk0/10/13/13/55 datestamp: 2021-07-19 16:27:11 lastmod: 2022-02-28 16:53:31 status_changed: 2021-07-19 16:27:11 type: article metadata_visibility: show creators_name: Becker, J creators_name: Burik, CAP creators_name: Goldman, G creators_name: Wang, N creators_name: Jayashankar, H creators_name: Bennett, M creators_name: Belsky, DW creators_name: Linner, RK creators_name: Ahlskog, R creators_name: Kleinman, A creators_name: Hinds, DA creators_name: Caspi, A creators_name: Corcoran, DL creators_name: Moffitt, TE creators_name: Poulton, R creators_name: Sugden, K creators_name: Williams, BS creators_name: Harris, KM creators_name: Steptoe, A creators_name: Ajnakina, O creators_name: Milani, L creators_name: Esko, T creators_name: Iacono, WG creators_name: McGue, M creators_name: Magnusson, PKE creators_name: Mallard, TT creators_name: Harden, KP creators_name: Tucker-Drob, EM creators_name: Herd, P creators_name: Freese, J creators_name: Young, A creators_name: Beauchamp, JP creators_name: Koellinger, P creators_name: Oskarsson, S creators_name: Johannesson, M creators_name: Visscher, PM creators_name: Meyer, MN creators_name: Laibson, D creators_name: Cesarini, D creators_name: Benjamin, DJ creators_name: Turley, P creators_name: Okbay, A title: Resource profile and user guide of the Polygenic Index Repository ispublished: pub divisions: UCL divisions: B02 divisions: D12 divisions: J96 keywords: Behavioural genetics, Economics, Genome-wide association studies, Human behaviour note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. abstract: Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is growing rapidly. 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 this 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. date: 2021-12 date_type: published publisher: NATURE RESEARCH official_url: https://doi.org/10.1038/s41562-021-01119-3 oa_status: green full_text_type: other language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 1872659 doi: 10.1038/s41562-021-01119-3 lyricists_name: Ajnakina, Olesya lyricists_name: Steptoe, Andrew lyricists_id: OAJNA31 lyricists_id: ASTEP39 actors_name: Ajnakina, Olesya actors_id: OAJNA31 actors_role: owner full_text_status: public publication: Nature Human Behaviour volume: 5 pagerange: 1744-1758 pages: 17 citation: Becker, J; Burik, CAP; Goldman, G; Wang, N; Jayashankar, H; Bennett, M; Belsky, DW; ... Okbay, A; + view all <#> Becker, J; Burik, CAP; Goldman, G; Wang, N; Jayashankar, H; Bennett, M; Belsky, DW; Linner, RK; Ahlskog, R; Kleinman, A; Hinds, DA; Caspi, A; Corcoran, DL; Moffitt, TE; Poulton, R; Sugden, K; Williams, BS; Harris, KM; Steptoe, A; Ajnakina, O; Milani, L; Esko, T; Iacono, WG; McGue, M; Magnusson, PKE; Mallard, TT; Harden, KP; Tucker-Drob, EM; Herd, P; Freese, J; Young, A; Beauchamp, JP; Koellinger, P; Oskarsson, S; Johannesson, M; Visscher, PM; Meyer, MN; Laibson, D; Cesarini, D; Benjamin, DJ; Turley, P; Okbay, A; - view fewer <#> (2021) Resource profile and user guide of the Polygenic Index Repository. Nature Human Behaviour , 5 pp. 1744-1758. 10.1038/s41562-021-01119-3 <https://doi.org/10.1038/s41562-021-01119-3>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10131355/1/PGI%20Repository%20paper.pdf