Resource profile and user guide of the Polygenic Index Repository.

Szczegóły
Abstrakt

Tytuł:: Resource profile and user guide of the Polygenic Index Repository.
Autorzy:: Becker J; Department of Economics, New York University, New York, NY, USA.
Burik CAP; Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Goldman G; National Bureau of Economic Research, Cambridge, MA, USA.
Wang N; National Bureau of Economic Research, Cambridge, MA, USA.
Jayashankar H; National Bureau of Economic Research, Cambridge, MA, USA.
Bennett M; National Bureau of Economic Research, Cambridge, MA, USA.
Belsky DW; Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA.; Robert N. Butler Columbia Aging Center, Columbia University, New York, NY, USA.
Karlsson Linnér R; Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Ahlskog R; Department of Government, Uppsala University, Uppsala, Sweden.
Kleinman A; 23andMe, Inc., Mountain View, CA, USA.
Hinds DA; 23andMe, Inc., Mountain View, CA, USA.
Caspi A; Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.; Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.; Center for Genomic and Computational Biology, Duke University, Durham, NC, USA.; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA.
Corcoran DL; Center for Genomic and Computational Biology, Duke University, Durham, NC, USA.
Moffitt TE; Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.; Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.; Center for Genomic and Computational Biology, Duke University, Durham, NC, USA.; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA.
Poulton R; Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin, New Zealand.
Sugden K; Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.
Williams BS; Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.
Harris KM; Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.; Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Steptoe A; Department of Behavioural Science and Health, University College London, London, UK.
Ajnakina O; Department of Behavioural Science and Health, University College London, London, UK.; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK.
Milani L; Institute of Genomics, University of Tartu, Tartu, Estonia.
Esko T; Institute of Genomics, University of Tartu, Tartu, Estonia.; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Iacono WG; Department of Psychology, University of Minnesota, Minneapolis, MN, USA.
McGue M; Department of Psychology, University of Minnesota, Minneapolis, MN, USA.
Magnusson PKE; Swedish Twin Registry, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Mallard TT; Department of Psychology, The University of Texas at Austin, Austin, TX, USA.
Harden KP; Department of Psychology, The University of Texas at Austin, Austin, TX, USA.; Population Research Center, The University of Texas at Austin, Austin, TX, USA.
Tucker-Drob EM; Department of Psychology, The University of Texas at Austin, Austin, TX, USA.; Population Research Center, The University of Texas at Austin, Austin, TX, USA.
Herd P; McCourt School of Public Policy, Georgetown University, Washington, DC, USA.
Freese J; Department of Sociology, Stanford University, Stanford, CA, USA.
Young A; UCLA Anderson School of Management, Los Angeles, CA, USA.; Human Genetics Department, UCLA David Geffen School of Medicine, Los Angeles, CA, USA.
Beauchamp JP; Interdisciplinary Center for Economic Science and Department of Economics, George Mason University, Fairfax, VA, USA.
Koellinger PD; Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.; Robert M. La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI, USA.
Oskarsson S; Department of Government, Uppsala University, Uppsala, Sweden.
Johannesson M; Department of Economics, Stockholm School of Economics, Stockholm, Sweden.
Visscher PM; Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
Meyer MN; Center for Translational Bioethics and Health Care Policy, Geisinger Health System, Danville, PA, USA.
Laibson D; National Bureau of Economic Research, Cambridge, MA, USA.; Department of Economics, Harvard University, Cambridge, MA, USA.
Cesarini D; Department of Economics, New York University, New York, NY, USA. .; National Bureau of Economic Research, Cambridge, MA, USA. .
Benjamin DJ; National Bureau of Economic Research, Cambridge, MA, USA. .; UCLA Anderson School of Management, Los Angeles, CA, USA. .; Human Genetics Department, UCLA David Geffen School of Medicine, Los Angeles, CA, USA. .
Turley P; Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA. .; Department of Economics, University of Southern California, Los Angeles, CA, USA. .
Okbay A; Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands. .
Corporate Authors:: 23andMe Research Group
Źródło:: Nature human behaviour [Nat Hum Behav] 2021 Dec; Vol. 5 (12), pp. 1744-1758. Date of Electronic Publication: 2021 Jun 17.
Typ publikacji:: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
Język:: English
Imprint Name(s):: Original Publication: [London] : Springer Nature Publishing, [2017]-
MeSH Terms:: Databases, Genetic*
Multifactorial Inheritance*
Polymorphism, Single Nucleotide*
Data Analysis ; Genome-Wide Association Study ; Humans
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Grant Information:: MR/P005918/1 United Kingdom MRC_ Medical Research Council; R24 AG065184 United States AG NIA NIH HHS; R00 AG062787 United States AG NIA NIH HHS; P2C HD042849 United States HD NICHD NIH HHS; U01 MH109539 United States MH NIMH NIH HHS; R01 MH101244 United States MH NIMH NIH HHS; R01 AG042568 United States AG NIA NIH HHS; R56 AG058726 United States AG NIA NIH HHS; MC_PC_17228 United Kingdom MRC_ Medical Research Council; K99 AG062787 United States AG NIA NIH HHS; R01 HD083613 United States HD NICHD NIH HHS; G1002190 United Kingdom MRC_ Medical Research Council; MC_QA137853 United Kingdom MRC_ Medical Research Council; R01 HD092548 United States HD NICHD NIH HHS
Contributed Indexing:: Investigator: M Agee; B Alipanahi; A Auton; RK Bell; K Bryc; SL Elson; P Fontanillas; NA Furlotte; KE Huber; NK Litterman; JC McCreight; MH McIntyre; JL Mountain; CAM Northover; SJ Pitts; JF Sathirapongsasuti; OV Sazonova; JF Shelton; S Shringarpure; C Tian; JY Tung; V Vacic; CH Wilson
Entry Date(s):: Date Created: 20210618 Date Completed: 20220221 Latest Revision: 20240404
Update Code:: 20240404
PubMed Central ID:: PMC8678380
DOI:: 10.1038/s41562-021-01119-3
PMID:: 34140656
: Czasopismo naukowe

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.
(© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

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