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Connecting genetic risk to disease end points through the human blood plasma proteome
by
Al-Dous, Eman K.
, Wahl, Annika
, Mohamoud, Yasmin A.
, Grallert, Harald
, Arnold, Matthias
, Bhagwat, Aditya Mukund
, Peters, Annette
, Thareja, Gaurav
, Raffler, Johannes
, Pezer, Marija
, Engelke, Rudolf
, Cotton, Richard J.
, Sarwath, Hina
, Gold, Larry
, DeLisle, Robert Kirk
, Malek, Joel
, Mook-Kanamori, Dennis O.
, El-Din Selim, Mohammed A.
, Suhre, Karsten
, Strauch, Konstantin
, Graumann, Johannes
, Gieger, Christian
, Kastenmüller, Gabi
, Lauc, Gordan
in
631/208/205/2138
/ 631/45/475
/ 82/47
/ Alleles
/ Alzheimer's disease
/ Blood Proteins - metabolism
/ Cardiovascular disease
/ Complement System Proteins - metabolism
/ Diabetes
/ Drug Delivery Systems
/ Education
/ Endpoint Determination
/ Environmental health
/ Epidemiology
/ Gene Regulatory Networks
/ Genetic Predisposition to Disease
/ Genetic variance
/ Genetic Variation
/ Genome, Human
/ Genome-Wide Association Study
/ Genomes
/ Glycoproteins - metabolism
/ Health risk assessment
/ Heme - metabolism
/ Humanities and Social Sciences
/ Humans
/ Immunoassay
/ Metabolites
/ Molecular Sequence Annotation
/ multidisciplinary
/ Pharmacogenetics
/ Plasma
/ Protein Processing, Post-Translational - genetics
/ Proteins
/ Proteome - genetics
/ Proteome - metabolism
/ Proteomics
/ Quantitative Trait Loci
/ Reproducibility of Results
/ Research centers
/ Risk Factors
/ RNA Splicing - genetics
/ RNA, Messenger - genetics
/ RNA, Messenger - metabolism
/ Science
/ Science (multidisciplinary)
/ Scientific imaging
2017
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Connecting genetic risk to disease end points through the human blood plasma proteome
by
Al-Dous, Eman K.
, Wahl, Annika
, Mohamoud, Yasmin A.
, Grallert, Harald
, Arnold, Matthias
, Bhagwat, Aditya Mukund
, Peters, Annette
, Thareja, Gaurav
, Raffler, Johannes
, Pezer, Marija
, Engelke, Rudolf
, Cotton, Richard J.
, Sarwath, Hina
, Gold, Larry
, DeLisle, Robert Kirk
, Malek, Joel
, Mook-Kanamori, Dennis O.
, El-Din Selim, Mohammed A.
, Suhre, Karsten
, Strauch, Konstantin
, Graumann, Johannes
, Gieger, Christian
, Kastenmüller, Gabi
, Lauc, Gordan
in
631/208/205/2138
/ 631/45/475
/ 82/47
/ Alleles
/ Alzheimer's disease
/ Blood Proteins - metabolism
/ Cardiovascular disease
/ Complement System Proteins - metabolism
/ Diabetes
/ Drug Delivery Systems
/ Education
/ Endpoint Determination
/ Environmental health
/ Epidemiology
/ Gene Regulatory Networks
/ Genetic Predisposition to Disease
/ Genetic variance
/ Genetic Variation
/ Genome, Human
/ Genome-Wide Association Study
/ Genomes
/ Glycoproteins - metabolism
/ Health risk assessment
/ Heme - metabolism
/ Humanities and Social Sciences
/ Humans
/ Immunoassay
/ Metabolites
/ Molecular Sequence Annotation
/ multidisciplinary
/ Pharmacogenetics
/ Plasma
/ Protein Processing, Post-Translational - genetics
/ Proteins
/ Proteome - genetics
/ Proteome - metabolism
/ Proteomics
/ Quantitative Trait Loci
/ Reproducibility of Results
/ Research centers
/ Risk Factors
/ RNA Splicing - genetics
/ RNA, Messenger - genetics
/ RNA, Messenger - metabolism
/ Science
/ Science (multidisciplinary)
/ Scientific imaging
2017
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Connecting genetic risk to disease end points through the human blood plasma proteome
by
Al-Dous, Eman K.
, Wahl, Annika
, Mohamoud, Yasmin A.
, Grallert, Harald
, Arnold, Matthias
, Bhagwat, Aditya Mukund
, Peters, Annette
, Thareja, Gaurav
, Raffler, Johannes
, Pezer, Marija
, Engelke, Rudolf
, Cotton, Richard J.
, Sarwath, Hina
, Gold, Larry
, DeLisle, Robert Kirk
, Malek, Joel
, Mook-Kanamori, Dennis O.
, El-Din Selim, Mohammed A.
, Suhre, Karsten
, Strauch, Konstantin
, Graumann, Johannes
, Gieger, Christian
, Kastenmüller, Gabi
, Lauc, Gordan
in
631/208/205/2138
/ 631/45/475
/ 82/47
/ Alleles
/ Alzheimer's disease
/ Blood Proteins - metabolism
/ Cardiovascular disease
/ Complement System Proteins - metabolism
/ Diabetes
/ Drug Delivery Systems
/ Education
/ Endpoint Determination
/ Environmental health
/ Epidemiology
/ Gene Regulatory Networks
/ Genetic Predisposition to Disease
/ Genetic variance
/ Genetic Variation
/ Genome, Human
/ Genome-Wide Association Study
/ Genomes
/ Glycoproteins - metabolism
/ Health risk assessment
/ Heme - metabolism
/ Humanities and Social Sciences
/ Humans
/ Immunoassay
/ Metabolites
/ Molecular Sequence Annotation
/ multidisciplinary
/ Pharmacogenetics
/ Plasma
/ Protein Processing, Post-Translational - genetics
/ Proteins
/ Proteome - genetics
/ Proteome - metabolism
/ Proteomics
/ Quantitative Trait Loci
/ Reproducibility of Results
/ Research centers
/ Risk Factors
/ RNA Splicing - genetics
/ RNA, Messenger - genetics
/ RNA, Messenger - metabolism
/ Science
/ Science (multidisciplinary)
/ Scientific imaging
2017
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Connecting genetic risk to disease end points through the human blood plasma proteome
Journal Article
Connecting genetic risk to disease end points through the human blood plasma proteome
2017
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Overview
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.
Individual genetic variation can affect the levels of protein in blood, but detailed data sets linking these two types of data are rare. Here, the authors carry out a genome-wide association study of levels of over a thousand different proteins, and describe many new SNP-protein interactions.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
/ 82/47
/ Alleles
/ Complement System Proteins - metabolism
/ Diabetes
/ Genetic Predisposition to Disease
/ Genome-Wide Association Study
/ Genomes
/ Humanities and Social Sciences
/ Humans
/ Molecular Sequence Annotation
/ Plasma
/ Protein Processing, Post-Translational - genetics
/ Proteins
/ Science
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