Evidence map›Paper›PMID 38987645›Full record

ArticleNature aging2024

Blood protein assessment of leading incident diseases and mortality in the UK Biobank.

Danni A Gadd, Robert F Hillary, Zhana Kuncheva, Tasos Mangelis, Yipeng Cheng, Manju Dissanayake, Romi Admanit, Jake Gagnon, Tinchi Lin, Kyle L Ferber and 5 more

Abstract read
In one paragraph

Article in Nature aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers.

0numbers the graph read from it
0cells of the map it votes in
103citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

103 citing papers in PubMed.

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  7. Review
  8. Plasma Proteomic Profiles Predict Subsequent Obstructive Sleep Apnea Diagnosis in Adults With Metabolic Dysfunction-Associated Steatotic Liver Disease.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
    Article
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  19. Review
  20. Observational

43 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Danni A GaddOptima Partners, Edinburgh, UK.
Robert F HillaryOptima Partners, Edinburgh, UK.ORCID http://orcid.org/0000-0002-2595-552X
Zhana KunchevaOptima Partners, Edinburgh, UK.ORCID http://orcid.org/0000-0003-4057-6525
Tasos MangelisOptima Partners, Edinburgh, UK.
Yipeng ChengCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.ORCID http://orcid.org/0000-0003-0946-4525
Manju DissanayakeOptima Partners, Edinburgh, UK.
Romi AdmanitBiostatistics, Research and Development, Biogen Inc., Cambridge, MA, USA.
Jake GagnonBiostatistics, Research and Development, Biogen Inc., Cambridge, MA, USA.
Tinchi LinBiostatistics, Research and Development, Biogen Inc., Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-5098-6902
Kyle L FerberBiostatistics, Research and Development, Biogen Inc., Cambridge, MA, USA.
Heiko RunzTranslational Sciences, Research and Development, Biogen Inc., Cambridge, MA, USA.
Biogen Biobank Team
Christopher N Foley *Optima Partners, Edinburgh, UK. chris.foley@optimapartners.co.uk.ORCID http://orcid.org/0000-0002-0970-2610
Riccardo E Marioni *Optima Partners, Edinburgh, UK. riccardo.marioni@ed.ac.uk.ORCID http://orcid.org/0000-0003-4430-4260
Benjamin B Sun *Translational Sciences, Research and Development, Biogen Inc., Cambridge, MA, USA. bbsun92@outlook.com.ORCID http://orcid.org/0000-0001-6347-2281

Funding

Wellcome Trust
6 · The paper itself

Abstract

The circulating proteome offers insights into the biological pathways that underlie disease. Here, we test relationships between 1,468 Olink protein levels and the incidence of 23 age-related diseases and mortality in the UK Biobank (n = 47,600). We report 3,209 associations between 963 protein levels and 21 incident outcomes. Next, protein-based scores (ProteinScores) are developed using penalized Cox regression. When applied to test sets, six ProteinScores improve the area under the curve estimates for the 10-year onset of incident outcomes beyond age, sex and a comprehensive set of 24 lifestyle factors, clinically relevant biomarkers and physical measures. Furthermore, the ProteinScore for type 2 diabetes outperforms a polygenic risk score and HbA1c-a clinical marker used to monitor and diagnose type 2 diabetes. The performance of scores using metabolomic and proteomic features is also compared. These data characterize early proteomic contributions to major age-related diseases, demonstrating the value of the plasma proteome for risk stratification.

Indexed as

Blood ProteinsAdultAgedBiomarkersDiabetes Mellitus, Type 2FemaleHumansIncidenceMaleMiddle AgedProteomicsUK BiobankUnited KingdomBiomarkersBlood Proteins

Identifiers

PMID38987645
PMCPMC11257969

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.