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Genome-wide meta-analysis of 92 cardiometabolic protein serum levels

OBJECTIVES: Global cardiometabolic disease prevalence has grown rapidly over the years, making it the leading cause of death worldwide. Proteins are crucial components in biological pathways dysregulated in disease states. Identifying genetic components that influence circulating protein levels may...

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Autores principales: Gilly, Arthur, Park, Young-Chan, Tsafantakis, Emmanouil, Karaleftheri, Maria, Dedoussis, George, Zeggini, Eleftheria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10582065/
https://www.ncbi.nlm.nih.gov/pubmed/37778719
http://dx.doi.org/10.1016/j.molmet.2023.101810
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author Gilly, Arthur
Park, Young-Chan
Tsafantakis, Emmanouil
Karaleftheri, Maria
Dedoussis, George
Zeggini, Eleftheria
author_facet Gilly, Arthur
Park, Young-Chan
Tsafantakis, Emmanouil
Karaleftheri, Maria
Dedoussis, George
Zeggini, Eleftheria
author_sort Gilly, Arthur
collection PubMed
description OBJECTIVES: Global cardiometabolic disease prevalence has grown rapidly over the years, making it the leading cause of death worldwide. Proteins are crucial components in biological pathways dysregulated in disease states. Identifying genetic components that influence circulating protein levels may lead to the discovery of biomarkers for early stages of disease or offer opportunities as therapeutic targets. METHODS: Here, we carry out a genome-wide association study (GWAS) utilising whole genome sequencing data in 3,005 individuals from the HELIC founder populations cohort, across 92 proteins of cardiometabolic relevance. RESULTS: We report 322 protein quantitative trait loci (pQTL) signals across 92 proteins, of which 76 are located in or near the coding gene (cis-pQTL). We link those association signals with changes in protein expression and cardiometabolic disease risk using colocalisation and Mendelian randomisation (MR) analyses. CONCLUSIONS: The majority of previously unknown signals we describe point to proteins or protein interactions involved in inflammation and immune response, providing genetic evidence for the contributing role of inflammation in cardiometabolic disease processes.
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spelling pubmed-105820652023-10-19 Genome-wide meta-analysis of 92 cardiometabolic protein serum levels Gilly, Arthur Park, Young-Chan Tsafantakis, Emmanouil Karaleftheri, Maria Dedoussis, George Zeggini, Eleftheria Mol Metab Original Article OBJECTIVES: Global cardiometabolic disease prevalence has grown rapidly over the years, making it the leading cause of death worldwide. Proteins are crucial components in biological pathways dysregulated in disease states. Identifying genetic components that influence circulating protein levels may lead to the discovery of biomarkers for early stages of disease or offer opportunities as therapeutic targets. METHODS: Here, we carry out a genome-wide association study (GWAS) utilising whole genome sequencing data in 3,005 individuals from the HELIC founder populations cohort, across 92 proteins of cardiometabolic relevance. RESULTS: We report 322 protein quantitative trait loci (pQTL) signals across 92 proteins, of which 76 are located in or near the coding gene (cis-pQTL). We link those association signals with changes in protein expression and cardiometabolic disease risk using colocalisation and Mendelian randomisation (MR) analyses. CONCLUSIONS: The majority of previously unknown signals we describe point to proteins or protein interactions involved in inflammation and immune response, providing genetic evidence for the contributing role of inflammation in cardiometabolic disease processes. Elsevier 2023-09-29 /pmc/articles/PMC10582065/ /pubmed/37778719 http://dx.doi.org/10.1016/j.molmet.2023.101810 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Original Article
Gilly, Arthur
Park, Young-Chan
Tsafantakis, Emmanouil
Karaleftheri, Maria
Dedoussis, George
Zeggini, Eleftheria
Genome-wide meta-analysis of 92 cardiometabolic protein serum levels
title Genome-wide meta-analysis of 92 cardiometabolic protein serum levels
title_full Genome-wide meta-analysis of 92 cardiometabolic protein serum levels
title_fullStr Genome-wide meta-analysis of 92 cardiometabolic protein serum levels
title_full_unstemmed Genome-wide meta-analysis of 92 cardiometabolic protein serum levels
title_short Genome-wide meta-analysis of 92 cardiometabolic protein serum levels
title_sort genome-wide meta-analysis of 92 cardiometabolic protein serum levels
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10582065/
https://www.ncbi.nlm.nih.gov/pubmed/37778719
http://dx.doi.org/10.1016/j.molmet.2023.101810
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