Abstract
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.
| Original language | English (US) |
|---|---|
| Article number | 989 |
| Journal | Nature communications |
| Volume | 9 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 1 2018 |
ASJC Scopus subject areas
- General Physics and Astronomy
- General Chemistry
- General Biochemistry, Genetics and Molecular Biology
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In: Nature communications, Vol. 9, No. 1, 989, 01.12.2018.
Research output: Contribution to journal › Editorial › peer-review
}
TY - JOUR
T1 - Improving genetic prediction by leveraging genetic correlations among human diseases and traits
AU - Maier, Robert M.
AU - Zhu, Zhihong
AU - Lee, Sang Hong
AU - Trzaskowski, Maciej
AU - Ruderfer, Douglas M.
AU - Stahl, Eli A.
AU - Ripke, Stephan
AU - Wray, Naomi R.
AU - Yang, Jian
AU - Visscher, Peter M.
AU - Robinson, Matthew R.
AU - Forstner, Andreas J.
AU - Mcquillin, Andrew
AU - Trubetskoy, Vassily
AU - Wang, Weiqing
AU - Wang, Yunpeng
AU - Coleman, Jonathan R.I.
AU - Gaspar, Héléna A.
AU - De Leeuw, Christiaan A.
AU - Whitehead Pavlides, Jennifer M.
AU - Olde Loohuis, Loes M.
AU - Pers, Tune H.
AU - Lee, Phil H.
AU - Charney, Alexander W.
AU - Dobbyn, Amanda L.
AU - Huckins, Laura
AU - Boocock, James
AU - Giambartolomei, Claudia
AU - Roussos, Panos
AU - Mullins, Niamh
AU - Awasthi, Swapnil
AU - Agerbo, Esben
AU - Als, Thomas D.
AU - Pedersen, Carsten Bøcker
AU - Grove, Jakob
AU - Kupka, Ralph
AU - Regeer, Eline J.
AU - Anjorin, Adebayo
AU - Casas, Miquel
AU - Mahon, Pamela B.
AU - Allardyce, Judith
AU - Escott-Price, Valentina
AU - Forty, Liz
AU - Fraser, Christine
AU - Kogevinas, Manolis
AU - Frank, Josef
AU - Streit, Fabian
AU - Strohmaier, Jana
AU - Treutlein, Jens
AU - Witt, Stephanie H.
AU - Kennedy, James L.
AU - Strauss, John S.
AU - Garnham, Julie
AU - O'donovan, Claire
AU - Slaney, Claire
AU - Steinberg, Stacy
AU - Thorgeirsson, Thorgeir E.
AU - Hautzinger, Martin
AU - Steffens, Michael
AU - Perlis, Roy H.
AU - Sánchez-Mora, Cristina
AU - Hipolito, Maria
AU - Lawson, William B.
AU - Nwulia, Evaristus A.
AU - Levy, Shawn E.
AU - Foroud, Tatiana M.
AU - Jamain, Stéphane
AU - Young, Allan H.
AU - Mckay, James D.
AU - Albani, Diego
AU - Zandi, Peter
AU - Potash, James B.
AU - Zhang, Peng
AU - Raymond Depaulo, J.
AU - Bergen, Sarah E.
AU - Juréus, Anders
AU - Karlsson, Robert
AU - Kandaswamy, Radhika
AU - Mcguffin, Peter
AU - Rivera, Margarita
AU - Lissowska, Jolanta
AU - Cruceanu, Cristiana
AU - Lucae, Susanne
AU - Cervantes, Pablo
AU - Budde, Monika
AU - Gade, Katrin
AU - Heilbronner, Urs
AU - Pedersen, Marianne Giørtz
AU - Morris, Derek W.
AU - Weickert, Cynthia Shannon
AU - Weickert, Thomas W.
AU - Macintyre, Donald J.
AU - Lawrence, Jacob
AU - Elvsåshagen, Torbjørn
AU - Smeland, Olav B.
AU - Djurovic, Srdjan
AU - Xi, Simon
AU - Green, Elaine K.
AU - Czerski, Piotr M.
AU - Hauser, Joanna
AU - Xu, Wei
AU - Vedder, Helmut
AU - Oruc, Lilijana
AU - Spijker, Anne T.
AU - Gordon, Scott D.
AU - Medland, Sarah E.
AU - Curtis, David
AU - Mühleisen, Thomas W.
AU - Badner, Judith
AU - Scheftner, William A.
AU - Sigurdsson, Engilbert
AU - Schork, Nicholas J.
AU - Schatzberg, Alan F.
AU - Bækvad-Hansen, Marie
AU - Bybjerg-Grauholm, Jonas
AU - Hansen, Christine Søholm
AU - Knowles, James A.
AU - Szelinger, Szabolcs
AU - Montgomery, Grant W.
AU - Boks, Marco
AU - Adolfsson, Annelie Nordin
AU - Hoffmann, Per
AU - Bauer, Michael
AU - Pfennig, Andrea
AU - Leber, Markus
AU - Kittel-Schneider, Sarah
AU - Reif, Andreas
AU - Del-Favero, Jurgen
AU - Fischer, Sascha B.
AU - Herms, Stefan
AU - Reinbold, Céline S.
AU - Degenhardt, Franziska
AU - Koller, Anna C.
AU - Maaser, Anna
AU - Ori, Anil
AU - Dale, Anders M.
AU - Fan, Chun Chieh
AU - Greenwood, Tiffany A.
AU - Nievergelt, Caroline M.
AU - Shehktman, Tatyana
AU - Shilling, Paul D.
AU - Byerley, William
AU - Bunney, William
AU - Alliey-Rodriguez, Ney
AU - Clarke, Toni Kim
AU - Liu, Chunyu
AU - Coryell, William
AU - Akil, Huda
AU - Burmeister, Margit
AU - Flickinger, Matthew
AU - Li, Jun Z.
AU - Mcinnis, Melvin G.
AU - Meng, Fan
AU - Thompson, Robert C.
AU - Watson, Stanley J.
AU - Zollner, Sebastian
AU - Guan, Weihua
AU - Green, Melissa J.
AU - Craig, David
AU - Sobell, Janet L.
AU - Milani, Lili
AU - Gordon-Smith, Katherine
AU - Knott, Sarah V.
AU - Perry, Amy
AU - Parra, José Guzman
AU - Mayoral, Fermin
AU - Rivas, Fabio
AU - Rice, John P.
AU - Barchas, Jack D.
AU - Børglum, Anders D.
AU - Mortensen, Preben Bo
AU - Mors, Ole
AU - Grigoroiu-Serbanescu, Maria
AU - Bellivier, Frank
AU - Etain, Bruno
AU - Leboyer, Marion
AU - Ramos-Quiroga, Josep Antoni
AU - Agartz, Ingrid
AU - Amin, Farooq
AU - Azevedo, Maria H.
AU - Bass, Nicholas
AU - Black, Donald W.
AU - Blackwood, Douglas H.R.
AU - Bruggeman, Richard
AU - Buccola, Nancy G.
AU - Choudhury, Khalid
AU - Cloninger, C. Robert
AU - Corvin, Aiden
AU - Craddock, Nicholas
AU - Daly, Mark J.
AU - Datta, Susmita
AU - Donohoe, Gary J.
AU - Duan, Jubao
AU - Dudbridge, Frank
AU - Fanous, Ayman
AU - Freedman, Robert
AU - Freimer, Nelson B.
AU - Friedl, Marion
AU - Gill, Michael
AU - Gurling, Hugh
AU - De Haan, Lieuwe
AU - Hamshere, Marian L.
AU - Hartmann, Annette M.
AU - Holmans, Peter A.
AU - Kahn, René S.
AU - Keller, Matthew C.
AU - Kenny, Elaine
AU - Kirov, George K.
AU - Krabbendam, Lydia
AU - Krasucki, Robert
AU - Lencz, Todd
AU - Levinson, Douglas F.
AU - Lieberman, Jeffrey A.
AU - Lin, Dan Yu
AU - Linszen, Don H.
AU - Magnusson, Patrik K.E.
AU - Maier, Wolfgang
AU - Malhotra, Anil K.
AU - Mattheisen, Manuel
AU - Mattingsdal, Morten
AU - Mccarroll, Steven A.
AU - Medeiros, Helena
AU - Melle, Ingrid
AU - Milanova, Vihra
AU - Myin-Germeys, Inez
AU - Neale, Benjamin M.
AU - Ophoff, Roel A.
AU - Owen, Michael J.
AU - Pimm, Jonathan
AU - Purcell, Shaun M.
AU - Puri, Vinay
AU - Quested, Digby J.
AU - Rossin, Lizzy
AU - Sanders, Alan R.
AU - Shi, Jianxin
AU - Sklar, Pamela
AU - St Clair, David
AU - Stroup, T. Scott
AU - Van Os, Jim
AU - Wiersma, Durk
AU - Zammit, Stanley
N1 - Publisher Copyright: © 2018 The Author(s).
PY - 2018/12/1
Y1 - 2018/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85048198000&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85048198000&partnerID=8YFLogxK
U2 - 10.1038/s41467-017-02769-6
DO - 10.1038/s41467-017-02769-6
M3 - Editorial
C2 - 29515099
AN - SCOPUS:85048198000
SN - 2041-1723
VL - 9
JO - Nature communications
JF - Nature communications
IS - 1
M1 - 989
ER -