Connecting genetic risk to disease end points through the human blood plasma proteome
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...
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| Vydáno v: | Nature communications Ročník 8; číslo 1; s. 14357 - 14 |
|---|---|
| Hlavní autoři: | , , , , , , , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
London
Nature Publishing Group UK
27.02.2017
Nature Publishing Group Nature Portfolio |
| Témata: | |
| ISSN: | 2041-1723, 2041-1723 |
| On-line přístup: | Získat plný text |
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| 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.
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. |
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| AbstractList | 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. 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. 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.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. 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. 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. |
| ArticleNumber | 14357 |
| Author | 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 |
| Author_xml | – sequence: 1 givenname: Karsten orcidid: 0000-0001-9638-3912 surname: Suhre fullname: Suhre, Karsten email: karsten@suhre.fr organization: Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Education City – sequence: 2 givenname: Matthias orcidid: 0000-0002-4666-0923 surname: Arnold fullname: Arnold, Matthias organization: Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health – sequence: 3 givenname: Aditya Mukund surname: Bhagwat fullname: Bhagwat, Aditya Mukund organization: Proteomics Core, Weill Cornell Medicine-Qatar, Education City – sequence: 4 givenname: Richard J. surname: Cotton fullname: Cotton, Richard J. organization: Proteomics Core, Weill Cornell Medicine-Qatar, Education City – sequence: 5 givenname: Rudolf surname: Engelke fullname: Engelke, Rudolf organization: Proteomics Core, Weill Cornell Medicine-Qatar, Education City – sequence: 6 givenname: Johannes surname: Raffler fullname: Raffler, Johannes organization: Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health – sequence: 7 givenname: Hina surname: Sarwath fullname: Sarwath, Hina organization: Proteomics Core, Weill Cornell Medicine-Qatar, Education City – sequence: 8 givenname: Gaurav surname: Thareja fullname: Thareja, Gaurav organization: Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Education City – sequence: 9 givenname: Annika surname: Wahl fullname: Wahl, Annika organization: Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health – sequence: 10 givenname: Robert Kirk surname: DeLisle fullname: DeLisle, Robert Kirk organization: SomaLogic – sequence: 11 givenname: Larry surname: Gold fullname: Gold, Larry organization: SomaLogic – sequence: 12 givenname: Marija orcidid: 0000-0002-6480-1427 surname: Pezer fullname: Pezer, Marija organization: Genos Ltd, Glycoscience Research Laboratory – sequence: 13 givenname: Gordan surname: Lauc fullname: Lauc, Gordan organization: Genos Ltd, Glycoscience Research Laboratory – sequence: 14 givenname: Mohammed A. surname: El-Din Selim fullname: El-Din Selim, Mohammed A. organization: Department of Dermatology, Hamad Medical Corporation – sequence: 15 givenname: Dennis O. surname: Mook-Kanamori fullname: Mook-Kanamori, Dennis O. organization: Leiden University Medical Centre – sequence: 16 givenname: Eman K. surname: Al-Dous fullname: Al-Dous, Eman K. organization: Genomics Core, Weill Cornell Medicine-Qatar, Education City – sequence: 17 givenname: Yasmin A. surname: Mohamoud fullname: Mohamoud, Yasmin A. organization: Genomics Core, Weill Cornell Medicine-Qatar, Education City – sequence: 18 givenname: Joel surname: Malek fullname: Malek, Joel organization: Genomics Core, Weill Cornell Medicine-Qatar, Education City – sequence: 19 givenname: Konstantin surname: Strauch fullname: Strauch, Konstantin organization: Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität – sequence: 20 givenname: Harald surname: Grallert fullname: Grallert, Harald organization: Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, German Center for Diabetes Research (DZD) – sequence: 21 givenname: Annette surname: Peters fullname: Peters, Annette organization: Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, German Center for Diabetes Research (DZD), German Center for Cardiovascular Disease Research (DZHK) – sequence: 22 givenname: Gabi surname: Kastenmüller fullname: Kastenmüller, Gabi organization: Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, German Center for Diabetes Research (DZD) – sequence: 23 givenname: Christian surname: Gieger fullname: Gieger, Christian email: christian.gieger@helmholtz-muenchen.de organization: Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, German Center for Diabetes Research (DZD) – sequence: 24 givenname: Johannes orcidid: 0000-0002-3015-5850 surname: Graumann fullname: Graumann, Johannes email: johannes.graumann@mpi-bn.mpg.de organization: Proteomics Core, Weill Cornell Medicine-Qatar, Education City, Present address: Scientific Service Group Biomolecular Mass Spectrometry, Max Planck Institute for Heart and Lung Research, W.G. Kerckhoff Institute, Ludwigstr. 43, D-61231 Bad Nauheim, Germany |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28240269$$D View this record in MEDLINE/PubMed |
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| Snippet | Genome-wide association studies (GWAS) with intermediate phenotypes, like changes in metabolite and protein levels, provide functional evidence to map disease... 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... |
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| Title | Connecting genetic risk to disease end points through the human blood plasma proteome |
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