Evidence map›Paper›PMID 40709259›Full record

ArticleResearch square2025

Associations of proteomic age with mortality and incident chronic diseases in the European Prospective Investigation into Cancer and Nutrition (EPIC).

Oliver Robinson, Han Xiao, Jan Homann, Vivian Viallon, Pietro Ferrari, José M Huerta, Ana Jiménez Zabala, Rudolf Kaaks, Verena A Katzke, Claudia Langenberg and 16 more

Abstract readPreprint
In one paragraph

Article in Research square, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

26 authors.

Oliver RobinsonDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, UK.ORCID 0000-0002-4735-0468
Han XiaoDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, UK.
Jan HomannInstitute of Epidemiology and Social Medicine, University of Münster, Germany.ORCID 0000-0003-2791-7065
Vivian ViallonInternational Agency for Research on Cancer, France.
Pietro FerrariInternational Agency for Research on Cancer, France.
José M HuertaDepartment of Epidemiology, Murcia Regional Health Council-IMIB, 30007 Murcia, Spain.
Ana Jiménez ZabalaMinistry of Health of the Basque Government, Sub Directorate for Public Health and Addictions of Gipuzkoa, 20013 San Sebastian, Spain.
Rudolf KaaksDivision of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.ORCID 0000-0003-3751-3929
Verena A KatzkeDivision of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Claudia LangenbergPrecision Healthcare University Research Institute, Queen Mary University of London, UK.ORCID 0000-0002-5017-7344
ChungHo E LauDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, UK.ORCID 0000-0002-3602-8326
Lefkos MiddletonAgeing Epidemiology Research (AGE) Unit, School of Public Health, Imperial College London, UK.ORCID 0000-0002-2176-403X
N Charlotte Onland-MoretJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.ORCID 0000-0002-2360-913X
Salvatore PanicoFederico II University, Naples, Italy.
Anna PrizmentDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minnesota, USA.ORCID 0000-0001-5924-6871
Fulvio RicceriCentre for Biostatistics, Epidemiology, and Public Health (C-BEPH), Department of Clinical and Biological Sciences, University of Turin, Italy.
María-José SánchezEscuela Andaluza de Salud Pública (EASP), 18011 Granada, Spain.
Karl Smith ByrneCancer Epidemiology Unit, University of Oxford, UK.ORCID 0000-0002-1932-7463
Paolo VineisDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, UK.ORCID 0000-0001-8935-4566
W Monique VerschurenJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Roel VermeulenInstitute for Risk Assessment Sciences at Utrecht University.ORCID 0000-0003-4082-8163
Shuo WangDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minnesota, USA.
Nick WarehamMRC Epidemiology Unit, University of Cambridge, UK.ORCID 0000-0003-1422-2993
Christina M LillAgeing Epidemiology Research (AGE) Unit, School of Public Health, Imperial College London, UK.ORCID 0000-0002-2805-1307
Elio RiboliDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, UK.ORCID 0000-0001-6795-6080
Marc J GunterDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, UK.

Funding

University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UM1TR004405 · NCATS · UNIVERSITY OF MINNESOTA · PI Bruce R Blazar, Damien A Fair · 2023 to 2026
$30.8M
Proteomic aging in adults before and after cancer diagnosisR01CA267977 · NCI · UNIVERSITY OF MINNESOTA · PI PRIZMENT, ANNA · 2022 to 2024
$1.0M
NCATS NIH HHS UM1 TR004405NCI NIH HHS R01 CA267977
6 · The paper itself

Abstract

Assessment of biological ageing using proteomic clocks may enhance risk prediction and elucidate the molecular links between ageing and chronic diseases. Within a pre-diagnostic cohort of 17,473 Europeans with up to 28 years of follow-up, we examined associations of plasma SomaScan-based proteomic clocks, including organ-specific clocks, with 24 incident chronic diseases, all-cause mortality, and lifestyle risk factors. Global proteomic age gap (a composite biological age acceleration score combining previously published clocks) showed the strongest positive association of all tested clocks with all-cause mortality. Accelerated proteomic ageing was significantly associated with smoking, alcohol consumption, physical inactivity, and higher risk of cardiovascular diseases, dementia, and liver, upper aero-digestive tract, lung, and kidney cancers. Some organ-specific cancers were more strongly associated with their respective organ-specific age gaps. Mortality prediction by proteomic clocks was comparable in performance to classical lifestyle risk factors. In summary, proteomic clocks appear promising biomarkers of generalized age-related disease risk.

Indexed as

Agingaptamersbiological agebiological clockscancercardiovascular diseasediabetesneurodegenerationproteomicsrisk factorsrisk predictionSomaLogic

Identifiers

PMID40709259
PMCPMC12288520

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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.