Genome-wide analysis of 439 mass spectrometry-based proteomic profiles in a population of 15,035 Scottish individuals

Abstract Understanding the genetic architecture of the circulating proteome can help determine if a protein is causally linked to disease. Previous large-scale genome-wide association studies of proteins have mostly been conducted on pre-defined, targeted subsets of the proteome, and have often concentrated on low-abundance proteins, many of which don’t exert their main function in serum. Mass spectrometry-based proteomics facilitates the study of high-abundance proteins and their isoforms, focusing on proteins active in blood. In 15035 individuals from Generation Scotland, we perform genome-wide association studies of 439 highly abundant serum protein groups as identified and quantified by liquid chromatography tandem mass spectrometry. We identify 1553 independent SNP signals for 398 proteins ( P < 1.2×10 −10 ). Two-sample Mendelian Randomisation analyses are applied to test if the 398 proteins with significant SNP signals are causally associated with 79 common causes of morbidity and mortality. We report putative causal associations between 13 proteins and 17 outcomes, including neuropsychiatric and cardiovascular conditions. Large-scale genome-wide analyses of the high-abundance proteome complement targeted approaches for the discovery of causal pathways of disease.

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Journal
Nature Communications
Published
2026-09-09
DOI
https://doi.org/10.1038/s41467-026-76474-8
Primary Topic
Genetic Associations and Epidemiology
Type
article
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article

Genome-wide analysis of 439 mass spectrometry-based proteomic profiles in a population of 15,035 Scottish individuals

Aleksej Zelezniak, Andrew M. McIntosh, Arturas Grauslys, Anne Richmond et al.
Nature Communications
Genetic Associations and Epidemiology
article

Genome-wide analysis of 439 mass spectrometry-based proteomic profiles in a population of 15,035 Scottish individuals

Aleksej Zelezniak, Andrew M. McIntosh, Arturas Grauslys, Anne Richmond, Archie Campbell, Aleksandra D. Chybowska, Caroline Hayward, Riccardo E. Marioni, Camilla Drake, Markus Ralser, Hannah Grant, Jure Mur, Christoph B. Messner, David J. Porteous, Poppy Adkin, Charles Brigden, Spyros Vernardis, Josephine A. Robertson, Robert F. Hillary, Matthew White, Daniel L. McCartney, Hannah M. Smith
article en

Abstract

Abstract Understanding the genetic architecture of the circulating proteome can help determine if a protein is causally linked to disease. Previous large-scale genome-wide association studies of proteins have mostly been conducted on pre-defined, targeted subsets of the proteome, and have often concentrated on low-abundance proteins, many of which don’t exert their main function in serum. Mass spectrometry-based proteomics facilitates the study of high-abundance proteins and their isoforms, focusing on proteins active in blood. In 15035 individuals from Generation Scotland, we perform genome-wide association studies of 439 highly abundant serum protein groups as identified and quantified by liquid chromatography tandem mass spectrometry. We identify 1553 independent SNP signals for 398 proteins ( P < 1.2×10 −10 ). Two-sample Mendelian Randomisation analyses are applied to test if the 398 proteins with significant SNP signals are causally associated with 79 common causes of morbidity and mortality. We report putative causal associations between 13 proteins and 17 outcomes, including neuropsychiatric and cardiovascular conditions. Large-scale genome-wide analyses of the high-abundance proteome complement targeted approaches for the discovery of causal pathways of disease.

Nature Communications
King's College London (GB), The Francis Crick Institute (GB), Edinburgh Cancer Research (GB), London Cancer (GB), Alzheimer Scotland (GB), Swiss Finance Institute (CH), Chalmers University of Technology (SE), Charité - Universitätsmedizin Berlin (DE), University of Edinburgh (GB)
Good health and well-being
Openalex Percentile: Top 11%
Genetic Associations and Epidemiology
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