Polygenic indices and genetic data 

SBI contributors 

Prof. Dr. David Richter

Project description

Polygenic indexes (PGIs) — DNA-based predictors for individual phenotypes — have become essential tools across the biomedical and social sciences. Here we introduce Version 2 of the Polygenic Index Repository, a substantially expanded resource to facilitate research using PGIs. Our update increases the number of PGI phenotypes from 47 to 61 and the number of datasets from 11 to 20. All PGIs are generated using a consistent methodology. For many phenotypes, we leverage summary statistics from a GWAS meta-analysis with a larger sample than was available for the original release, thereby improving the PGI’s predictive accuracy. To enable more robust inferences, we provide imputed parental PGIs in all datasets with pairs of first-degree relatives and provide a framework for interpreting results from analyses that control for parental PGIs. 

Status

Active

Selected publications 

Alemu R, Terskaya A, Howell M, Guan J, Sands H, Kleinman A; 23andMe Research Team; Bann D, Morris T, Ploubidis GB, Fitzsimons E, Harris KM, Caspi A, Corcoran DL, Moffitt TE, Poulton R, Sugden K, Williams BS, Steptoe A, Ajnakina O, Vainik U, Esko T; Estonian Biobank Research Team; Campbell A, Hayward C, Iacono WG, McGue M, Krueger RF, Docherty AR, Shabalin AA, Hertwig R, Koellinger P, Richter D, Goebel J, Ahlskog R, Oskarsson S, Magnusson PKE, Harden KP, Tucker-Drob EM, Pahnke CKL, Maj C, Spinath FM, Herd P, Freese J, Laibson D, Meyer MN, Jala J, Cesarini D, Young AS, Turley P, Benjamin DJ, Okbay A. An Updated Polygenic Index Repository: Expanded Phenotypes, New Cohorts, and Improved Causal Inference. bioRxiv [Preprint]. 2025 Aug 14:2025.05.14.653986. DOI: 10.1101/2025.05.14.653986. PMID: 40463245; PMCID: PMC12132466.