Cited by 478Genetic Associations and EpidemiologyBioinformatics and Genomic NetworksAdvanced Proteomics Techniques and Applications

Genetics meets proteomics: perspectives for large population-based studies

Suhre, Karsten, McCarthy, Mark I., Schwenk, Jochen M.·2021·Nature Reviews Genetics

Abstract

Proteomic analysis of cells, tissues and body fluids has generated valuable insights into the complex processes influencing human biology. Proteins represent intermediate phenotypes for disease and provide insight into how genetic and non-genetic risk factors are mechanistically linked to clinical outcomes. Associations between protein levels and DNA sequence variants that colocalize with risk alleles for common diseases can expose disease-associated pathways, revealing novel drug targets and translational biomarkers. However, genome-wide, population-scale analyses of proteomic data are only now emerging. Here, we review current findings from studies of the plasma proteome and discuss their potential for advancing biomedical translation through the interpretation of genome-wide association analyses. We highlight the challenges faced by currently available technologies and provide perspectives relevant to their future application in large-scale biobank studies.

Integrity signals

Registry

Crossref · 10.1038/s41576-020-0268-2

Cites

151 of 151 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Integrating human genomics and proteomics can help elucidate disease mechanisms, identify clinical biomarkers and discover drug targets.

    “Integrating human genomics and proteomics can help elucidate disease mechanisms, identify clinical biomarkers and discover drug targets1–4.”
  • Major developments in mass spectrometry-based, antibody-based and aptamer-based proteomics over the past decade have enabled the robust quantification of thousands of proteins in single samples.

    “Major developments in mass spectrometry-based, antibody-based and aptamer-based proteomics over the past decade have enabled the robust quantification of thousands of proteins in single samples87–90.”

    From Measuring biological age using omics data (2022) · cites this paper as [88]

  • Protein levels are likely to be regulated post-transcriptionally rather than by regulating mRNA level.

    “The enrichment of coding-variants for pQTLs in cis and trans (Extended Data Fig.10c, Tables S3, S4, S5) suggests that protein levels are likely to be regulated post-transcriptionally rather than by regulating mRNA level30.”

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Suhre, K., McCarthy, M. I., & Schwenk, J. M.
Affiliations
  • Weill Cornell Medical College in Qatar (QA)
  • Centre for Human Genetics (GB)
  • Science for Life Laboratory (SE)
Corresponding author
  • Suhre, Karsten
  • Schwenk, Jochen M.
Venue
Nature Reviews Genetics
Published
2020-08-28
Volume
22
Issue
1
Pages
19-37
ISSN
  • 1471-0056 (ISSN-L)
  • 1471-0064
OpenAlex
W3082024297
Cited by
478
References
151
Citations by year
2026: 76 · 2025: 111 · 2024: 96 · 2023: 79 · 2022: 62 · 2021: 50 · 2020: 4
FWCI
7.20
Type
journal article
Language
en
Open access
closed
Locations
  • Nature Reviews Genetics (publishedVersion)
  • PubMed (publishedVersion)
Funders
National Institute for Health and Care Research (NF-SI-0617-10090)
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
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
Keywords
plasma proteome, proteogenomics, genome-wide association study, endophenotypes, biomarkers, therapeutic target, biobanks, genetic variants, circulating proteins, disease mechanisms
MeSH terms
Blood Proteins, Humans, Phenotype, Biomarkers, Proteome, Proteomics, Genome-Wide Association Study

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 ›

Are you an author, or do you see a problem with this page? Request a review