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Nat Commun. 2017 Feb 27;8:14357. doi: 10.1038/ncomms14357.

Connecting genetic risk to disease end points through the human blood plasma proteome.

Author information

1
Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Education City, PO 24144 Doha, Qatar.
2
Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany.
3
Proteomics Core, Weill Cornell Medicine-Qatar, Education City, PO 24144 Doha, Qatar.
4
Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany.
5
Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany.
6
SomaLogic, 2945 Wilderness Pl, Boulder, Colorado 80301, USA.
7
Genos Ltd, Glycoscience Research Laboratory, Hondlova 2/11, 10000 Zagreb, Croatia.
8
Department of Dermatology, Hamad Medical Corporation, PO Box 3050 Doha, Qatar.
9
Leiden University Medical Centre, PO Box 9600, 2300 RC Leiden, The Netherlands.
10
Genomics Core, Weill Cornell Medicine-Qatar, Education City, PO 24144, Doha, Qatar.
11
Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany.
12
Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Marchioninistraße 15, 81377 München, Germany.
13
German Center for Diabetes Research (DZD), Ingolstädter Landstraße 1, 85764 Neuherberg, Germany.
14
German Center for Cardiovascular Disease Research (DZHK), Oudenarder Straße 16, 13347 Berlin, Germany.

Abstract

Genome-wide association studies (GWAS) with intermediate phenotypes, like changes in metabolite and protein levels, provide functional evidence to map disease associations and translate them into clinical applications. However, although hundreds of genetic variants have been associated with complex disorders, the underlying molecular pathways often remain elusive. Associations with intermediate traits are key in establishing functional links between GWAS-identified risk-variants and disease end points. Here we describe a GWAS using a highly multiplexed aptamer-based affinity proteomics platform. We quantify 539 associations between protein levels and gene variants (pQTLs) in a German cohort and replicate over half of them in an Arab and Asian cohort. Fifty-five of the replicated pQTLs are located in trans. Our associations overlap with 57 genetic risk loci for 42 unique disease end points. We integrate this information into a genome-proteome network and provide an interactive web-tool for interrogations. Our results provide a basis for novel approaches to pharmaceutical and diagnostic applications.

PMID:
28240269
PMCID:
PMC5333359
DOI:
10.1038/ncomms14357
[Indexed for MEDLINE]
Free PMC Article

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