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When the proteome meets the metabolome observational and Mendelian randomization analyses
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.ORCID iD: 0000-0003-2891-9273
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.ORCID iD: 0000-0003-2247-8454
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2026 (English)In: Metabolism: Clinical and Experimental, ISSN 0026-0495, E-ISSN 1532-8600, Vol. 180, article id 156602Article in journal (Refereed) Published
Abstract [en]

Objective The basis for protein synthesis is the genetic code. Many of these proteins will affect intermediary metabolites by acting as enzymes, hormones, or by other actions. The aim of the present study was to assess the relationships of a large number of proteins with endogenous metabolites. Methods Plasma protein levels were measured by the proximity extension assay (PEA) and metabolites by mass spectrometry. Cross-sectional relationships of 242 proteins and 790 metabolites were evaluated in the EpiHealth and POEM studies using a discovery/validation approach. Genetic instruments identified in UK Biobank for protein levels (n = 1621) and genetics for metabolite levels (n = 777) in SCAPIS and EpiHealth were employed for Mendelian randomization (MR) analysis regarding putative causal associations. Results In the observational analyses, 20% of the evaluated pairwise protein-metabolite associations were found significant in both the discovery and validation samples. We could however only find support for causal effects in the MR analysis for <0.1% of the pairwise associations, representing 326 unique proteins. The R2 for the relationship between the MR and observational estimates was only 0.05. 37 protein-metabolite relationships that were significant in a congruent fashion in both the observational and MR analyses were identified. A searchable online protein vs metabolite atlas was created for the scientific community to use these results. We also give some examples where metabolites were used to enhance protein findings in cardiovascular epidemiological research. Conclusion This study provides a comprehensive assessment of a large number of protein- metabolite relationships using both observational and MR analyses, highlighting how these results could be used to enhance clinical research.

Place, publisher, year, edition, pages
Elsevier, 2026. Vol. 180, article id 156602
Keywords [en]
Proteomics, Metabolomics, Cardiovascular disease, UK Biobank, Genetics
National Category
Cardiology and Cardiovascular Disease
Identifiers
URN: urn:nbn:se:uu:diva-584199DOI: 10.1016/j.metabol.2026.156602ISI: 001742539000001Scopus ID: 2-s2.0-105035103905OAI: oai:DiVA.org:uu-584199DiVA, id: diva2:2052109
Note

Rui Zheng and Mario Delgado-Velandia contributed equally to this work.

Available from: 2026-04-10 Created: 2026-04-10 Last updated: 2026-05-05Bibliographically approved

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Zheng, RuiDelgado-Velandia, MarioSundström, JohanDekkers, KoenLundmark, PerFall, ToveLind, Lars

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