--- _id: '7716' abstract: - lang: eng text: Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7% for height to 47% for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. article_number: '989' article_processing_charge: No article_type: original author: - first_name: Robert M. full_name: Maier, Robert M. last_name: Maier - first_name: Zhihong full_name: Zhu, Zhihong last_name: Zhu - first_name: Sang Hong full_name: Lee, Sang Hong last_name: Lee - first_name: Maciej full_name: Trzaskowski, Maciej last_name: Trzaskowski - first_name: Douglas M. full_name: Ruderfer, Douglas M. last_name: Ruderfer - first_name: Eli A. full_name: Stahl, Eli A. last_name: Stahl - first_name: Stephan full_name: Ripke, Stephan last_name: Ripke - first_name: Naomi R. full_name: Wray, Naomi R. last_name: Wray - first_name: Jian full_name: Yang, Jian last_name: Yang - first_name: Peter M. full_name: Visscher, Peter M. last_name: Visscher - first_name: Matthew Richard full_name: Robinson, Matthew Richard id: E5D42276-F5DA-11E9-8E24-6303E6697425 last_name: Robinson orcid: 0000-0001-8982-8813 citation: ama: Maier RM, Zhu Z, Lee SH, et al. Improving genetic prediction by leveraging genetic correlations among human diseases and traits. Nature Communications. 2018;9. doi:10.1038/s41467-017-02769-6 apa: Maier, R. M., Zhu, Z., Lee, S. H., Trzaskowski, M., Ruderfer, D. M., Stahl, E. A., … Robinson, M. R. (2018). Improving genetic prediction by leveraging genetic correlations among human diseases and traits. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-017-02769-6 chicago: Maier, Robert M., Zhihong Zhu, Sang Hong Lee, Maciej Trzaskowski, Douglas M. Ruderfer, Eli A. Stahl, Stephan Ripke, et al. “Improving Genetic Prediction by Leveraging Genetic Correlations among Human Diseases and Traits.” Nature Communications. Springer Nature, 2018. https://doi.org/10.1038/s41467-017-02769-6. ieee: R. M. Maier et al., “Improving genetic prediction by leveraging genetic correlations among human diseases and traits,” Nature Communications, vol. 9. Springer Nature, 2018. ista: Maier RM, Zhu Z, Lee SH, Trzaskowski M, Ruderfer DM, Stahl EA, Ripke S, Wray NR, Yang J, Visscher PM, Robinson MR. 2018. Improving genetic prediction by leveraging genetic correlations among human diseases and traits. Nature Communications. 9, 989. mla: Maier, Robert M., et al. “Improving Genetic Prediction by Leveraging Genetic Correlations among Human Diseases and Traits.” Nature Communications, vol. 9, 989, Springer Nature, 2018, doi:10.1038/s41467-017-02769-6. short: R.M. Maier, Z. Zhu, S.H. Lee, M. Trzaskowski, D.M. Ruderfer, E.A. Stahl, S. Ripke, N.R. Wray, J. Yang, P.M. Visscher, M.R. Robinson, Nature Communications 9 (2018). date_created: 2020-04-30T10:42:29Z date_published: 2018-03-07T00:00:00Z date_updated: 2021-01-12T08:15:03Z day: '07' doi: 10.1038/s41467-017-02769-6 extern: '1' intvolume: ' 9' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1038/s41467-017-02769-6 month: '03' oa: 1 oa_version: Published Version publication: Nature Communications publication_identifier: issn: - 2041-1723 publication_status: published publisher: Springer Nature quality_controlled: '1' status: public title: Improving genetic prediction by leveraging genetic correlations among human diseases and traits type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 9 year: '2018' ...