Genome-wide analysis of 439 mass spectrometry-based proteomic profiles in a population of 15,035 Scottish individuals Article Swipe
Anne Richmond
,
Janet Robertson
,
Hannah M. Smith
,
Robert F. Hillary
,
Aleksej Zelezniak
,
Spyros I. Vernardis
,
Aleksandra D. Chybowska
,
Arturas Grauslys
,
Jure Mur
,
A.M. Campbell
,
Camilla Drake
,
Hannah Grant
,
Poppy Adkin
,
Matthew White
,
Charles Brigden
,
Christoph B. Messner
,
David J. Porteous
,
Caroline Hayward
,
Andrew M. McIntosh
,
Daniel L. McCartney
,
Markus Ralser
,
Riccardo E. Marioni
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.08.14.25333677
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.08.14.25333677
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 (GWAS) of proteins have mostly been conducted to 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, focussing on proteins active in blood. In 15,035 individuals from Generation Scotland, we performed GWAS of 439 highly abundant serum protein groups as identified and quantified by liquid chromatography tandem mass spectrometry. We identified 1,553 independent SNP signals for 398 proteins (P Bonferroni < 1.2×10 −10 ). Two-sample Mendelian Randomisation (MR) analyses were applied to test if the 398 proteins with significant SNP signals were 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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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1101/2025.08.14.25333677
- https://www.medrxiv.org/content/medrxiv/early/2025/08/15/2025.08.14.25333677.full.pdf
- OA Status
- green
- Cited By
- 1
- References
- 69
- Related Works
- 10
- OpenAlex ID
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- OpenAlex ID
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https://openalex.org/W4413341050Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2025.08.14.25333677Digital Object Identifier
- Title
-
Genome-wide analysis of 439 mass spectrometry-based proteomic profiles in a population of 15,035 Scottish individualsWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-08-15Full publication date if available
- Authors
-
Anne Richmond, Janet Robertson, Hannah M. Smith, Robert F. Hillary, Aleksej Zelezniak, Spyros I. Vernardis, Aleksandra D. Chybowska, Arturas Grauslys, Jure Mur, A.M. Campbell, Camilla Drake, Hannah Grant, Poppy Adkin, Matthew White, Charles Brigden, Christoph B. Messner, David J. Porteous, Caroline Hayward, Andrew M. McIntosh, Daniel L. McCartney, Markus Ralser, Riccardo E. MarioniList of authors in order
- Landing page
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https://doi.org/10.1101/2025.08.14.25333677Publisher landing page
- PDF URL
-
https://www.medrxiv.org/content/medrxiv/early/2025/08/15/2025.08.14.25333677.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
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-
greenOpen access status per OpenAlex
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https://www.medrxiv.org/content/medrxiv/early/2025/08/15/2025.08.14.25333677.full.pdfDirect OA link when available
- Concepts
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Mass spectrometry, Computational biology, Population, Genome, Biology, Genetics, Medicine, Chemistry, Chromatography, Environmental health, GeneTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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