An atlas of genetic scores to predict multi-omic traits

Yu Xu, Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. yx322@medschl.cam.ac.uk.
Scott C. Ritchie, Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Yujian Liang, Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
Paul R. Timmers, Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK.
Maik Pietzner, MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK.
Loïc Lannelongue, Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Samuel A. Lambert, Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Usman A. Tahir, Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Sebastian May-Wilson, Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK.
Carles Foguet, Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Åsa Johansson, Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
Praveen Surendran, British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Artika P. Nath, Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Elodie Persyn, Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
James E. Peters, Department of Immunology and Inflammation, Faculty of Medicine, Imperial College London, London, UK.
Clare Oliver-Williams, British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Shuliang Deng, Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Bram Prins, British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Jian'an Luan, MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK.
Lorenzo Bomba, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Nicole Soranzo, British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Emanuele Di Angelantonio, British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Nicola Pirastu, Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK.
E Shyong Tai, Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
Rob M. van Dam, Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
Helen Parkinson, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK.
Emma E. Davenport, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Dirk S. Paul, British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Christopher Yau, Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK.
Robert E. Gerszten, Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Anders Mälarstig, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
John Danesh, British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Document Type

Journal Article

Publication Date

4-1-2023

Journal

Nature

Volume

616

Issue

7955

DOI

10.1038/s41586-023-05844-9

Abstract

The use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics. Here we examine a large cohort (the INTERVAL study; n = 50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, n = 3,175; Olink, n = 4,822), plasma metabolomics (Metabolon HD4, n = 8,153), serum metabolomics (Nightingale, n = 37,359) and whole-blood Illumina RNA sequencing (n = 4,136), and use machine learning to train genetic scores for 17,227 molecular traits, including 10,521 that reach Bonferroni-adjusted significance. We evaluate the performance of genetic scores through external validation across cohorts of individuals of European, Asian and African American ancestries. In addition, we show the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of the UK Biobank to identify disease associations using a phenome-wide scan. We highlight a series of biological insights with regard to genetic mechanisms in metabolism and canonical pathway associations with disease; for example, JAK-STAT signalling and coronary atherosclerosis. Finally, we develop a portal ( https://www.omicspred.org/ ) to facilitate public access to all genetic scores and validation results, as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores.

Department

Exercise and Nutrition Sciences

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