---
_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'
...