TY  - JOUR
TI  - Resource profile and user guide of the Polygenic Index Repository
KW  - Behavioural genetics
KW  -  Economics
KW  -  Genome-wide association studies
KW  -  Human behaviour
UR  - https://doi.org/10.1038/s41562-021-01119-3
SP  - 1744
JF  - Nature Human Behaviour
EP  - 1758
AV  - public
ID  - discovery10131355
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
A1  - Becker, J
A1  - Burik, CAP
A1  - Goldman, G
A1  - Wang, N
A1  - Jayashankar, H
A1  - Bennett, M
A1  - Belsky, DW
A1  - Linner, RK
A1  - Ahlskog, R
A1  - Kleinman, A
A1  - Hinds, DA
A1  - Caspi, A
A1  - Corcoran, DL
A1  - Moffitt, TE
A1  - Poulton, R
A1  - Sugden, K
A1  - Williams, BS
A1  - Harris, KM
A1  - Steptoe, A
A1  - Ajnakina, O
A1  - Milani, L
A1  - Esko, T
A1  - Iacono, WG
A1  - McGue, M
A1  - Magnusson, PKE
A1  - Mallard, TT
A1  - Harden, KP
A1  - Tucker-Drob, EM
A1  - Herd, P
A1  - Freese, J
A1  - Young, A
A1  - Beauchamp, JP
A1  - Koellinger, P
A1  - Oskarsson, S
A1  - Johannesson, M
A1  - Visscher, PM
A1  - Meyer, MN
A1  - Laibson, D
A1  - Cesarini, D
A1  - Benjamin, DJ
A1  - Turley, P
A1  - Okbay, A
PB  - NATURE RESEARCH
VL  - 5
Y1  - 2021/12//
N2  - 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.
ER  -