Connecting genetic risk to disease end points through the human blood plasma proteome
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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.
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Of the 278 pQTLs, 21 (7.55%) were tested in the Suhre et al. study; 12 (57.14%) were significant at Benjamini-Hochberg FDR < 0.05 and all significant pQTLs were directionally concordant.
“7.55% (21/278) pQTLs were also tested in the Suhre et al. study51 and 57.14% (12/21) were significant (Benjamini–Hochberg FDR < 0.05), and all the significant pQTLs were directionally concordant with the current study (Supplementary Table S2).”
From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [51]
Most pQTL studies have been conducted using serum or plasma measurements from blood samples, and only a limited number of studies has involved examination of liver and brain tissue-specific pQTLs.
“Second, most pQTL studies have been conducted using serum or plasma measurements from blood samples4,6,8,51 and only a limited number of studies has involved the examination of liver and brain tissue–specific pQTLs88,89.”
From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [51]
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- Authors
- Suhre, K., Arnold, M., Bhagwat, A. M., Cotton, R. J., Engelke, R., Raffler, J., Sarwath, H., Thareja, G., Wahl, A., DeLisle, R. K., Gold, L., Pezer, M., Lauc, G., El-Din Selim, M. A., Mook-Kanamori, D. O., Al-Dous, E. K., Mohamoud, Y. A., Malek, J., Strauch, K., Grallert, H., Peters, A., Kastenmüller, G., Gieger, C., & Graumann, J.
- Affiliations
- Weill Cornell Medical College in Qatar (QA)
- Helmholtz Munich (DE)
- SomaLogic (United States) (US)
- Genos (Croatia) (HR)
- Corresponding author
- Suhre, Karsten
- Gieger, Christian
- Graumann, Johannes
- ORCID
- Venue
- Nature Communications
- Published
- 2017-02-27
- Volume
- 8
- Issue
- 1
- Pages
- 14357-14357
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC5333359
- OpenAlex
- W2566116513
- Cited by
- 800
- References
- 11
- Citations by year
- 2026: 75 · 2025: 129 · 2024: 163 · 2023: 90 · 2022: 96 · 2021: 87 · 2020: 68 · 2019: 53 · 2018: 30 · 2017: 8 · 2014: 1
- FWCI
- 28.92
- Type
- journal article
- Language
- en
- Update notices
- erratum (2017-04-11)
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
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- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Open access LMU (Ludwid Maxmilian's Universitat Munchen) (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- Site cant be reached (submittedVersion, cc-by)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion, cc-by)
- Funders
- Qatar Foundation
- ZonMw (91614023, VENI Grant 916.14.023)
- Bundesministerium für Bildung und Forschung
- Weill Cornell Medical College
- Weill Cornell Medicine - Qatar
- Helmholtz Zentrum München
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- protein quantitative trait loci, plasma proteome, genetic risk variants, endophenotypes, trans-eQTL, replication of genetic associations, functional genomics
- MeSH terms
- Alleles, Blood Proteins, Complement System Proteins, Glycoproteins, Heme, Humans, Pharmacogenetics, Protein Processing, Post-Translational, Risk Factors, RNA Splicing, RNA, Messenger, Genetic Variation, Reproducibility of Results, Genome, Human, Drug Delivery Systems, Genetic Predisposition to Disease, Proteome, Endpoint Determination, Quantitative Trait Loci, Gene Regulatory Networks, Genome-Wide Association Study, Molecular Sequence Annotation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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