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Nature. 2018 Jun;558(7708):73-79. doi: 10.1038/s41586-018-0175-2. Epub 2018 Jun 6.

Genomic atlas of the human plasma proteome.

Author information

1
MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
2
MRL, Merck & Co., Inc., Kenilworth, NJ, USA.
3
Celgene Inc., Cambridge, MA, USA.
4
British Heart Foundation Cambridge Centre of Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge, UK.
5
MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
6
National Centre for Epidemiology and Population Health, The Australian National University, Canberra, Australian Capital Territory, Australia.
7
Homerton College, Cambridge, UK.
8
SomaLogic Inc, Boulder, CO, USA.
9
Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
10
Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
11
Division of Respiratory Medicine, Department of Medicine, University of Cambridge, Cambridge, UK.
12
NIHR Cambridge Biomedical Research Centre/BioResource, Cambridge University Hospitals, Cambridge, UK.
13
National Health Service (NHS) Blood and Transplant and Radcliffe Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, John Radcliffe Hospital, Oxford, UK.
14
BRC Haematology Theme and Department of Haematology, Churchill Hospital, Oxford, UK.
15
Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
16
National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK.
17
Department of Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
18
NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
19
JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK.
20
Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Doha, Qatar.
21
MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. jd292@medschl.cam.ac.uk.
22
British Heart Foundation Cambridge Centre of Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge, UK. jd292@medschl.cam.ac.uk.
23
Department of Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. jd292@medschl.cam.ac.uk.
24
NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. jd292@medschl.cam.ac.uk.
25
Biogen Inc., Cambridge, MA, USA.
26
MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. asb38@medschl.cam.ac.uk.
27
NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. asb38@medschl.cam.ac.uk.

Abstract

Although plasma proteins have important roles in biological processes and are the direct targets of many drugs, the genetic factors that control inter-individual variation in plasma protein levels are not well understood. Here we characterize the genetic architecture of the human plasma proteome in healthy blood donors from the INTERVAL study. We identify 1,927 genetic associations with 1,478 proteins, a fourfold increase on existing knowledge, including trans associations for 1,104 proteins. To understand the consequences of perturbations in plasma protein levels, we apply an integrated approach that links genetic variation with biological pathway, disease, and drug databases. We show that protein quantitative trait loci overlap with gene expression quantitative trait loci, as well as with disease-associated loci, and find evidence that protein biomarkers have causal roles in disease using Mendelian randomization analysis. By linking genetic factors to diseases via specific proteins, our analyses highlight potential therapeutic targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development.

PMID:
29875488
DOI:
10.1038/s41586-018-0175-2
[Indexed for MEDLINE]

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