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Integrative metabolomics differentiate coronary artery disease, peripheral artery disease, and venous thromboembolism risks
RATIONALE: Arterial and venous cardiovascular conditions, such as coronary artery disease (CAD), peripheral artery disease (PAD), and venous thromboembolism (VTE), are genetically correlated. Interrogating distinct and overlapping mechanisms may shed new light on disease mechanisms. OBJECTIVE: In th...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10327201/ https://www.ncbi.nlm.nih.gov/pubmed/37425786 http://dx.doi.org/10.1101/2023.06.21.23291103 |
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author | Lee, Jiwoo Gilliland, Thomas Koyama, Satoshi Nakao, Tetsushi Dron, Jacqueline Lannery, Kim Wong, Megan Peloso, Gina M. Hornsby, Whitney Natarajan, Pradeep |
author_facet | Lee, Jiwoo Gilliland, Thomas Koyama, Satoshi Nakao, Tetsushi Dron, Jacqueline Lannery, Kim Wong, Megan Peloso, Gina M. Hornsby, Whitney Natarajan, Pradeep |
author_sort | Lee, Jiwoo |
collection | PubMed |
description | RATIONALE: Arterial and venous cardiovascular conditions, such as coronary artery disease (CAD), peripheral artery disease (PAD), and venous thromboembolism (VTE), are genetically correlated. Interrogating distinct and overlapping mechanisms may shed new light on disease mechanisms. OBJECTIVE: In this study, we aimed to: identify and compare (1) epidemiologic and (2) causal, genetic relationships between metabolites and CAD, PAD, and VTE. METHODS: We used metabolomic data from 95,402 individuals in the UK Biobank, excluding individuals with prevalent cardiovascular disease. Logistic regression models adjusted for age, sex, genotyping array, first five principal components of ancestry, and statin use estimated the epidemiologic associations of 249 metabolites with incident CAD, PAD, or VTE. Bidirectional two-sample Mendelian randomization (MR) estimated the causal effects between metabolites and cardiovascular phenotypes using genome-wide association summary statistics for metabolites (N = 118,466 from UK Biobank), CAD (N = 184,305 from CARDIoGRAMplusC4D 2015), PAD (N = 243,060 from Million Veterans Project) and VTE (N = 650,119 from Million Veterans Project). Multivariable MR (MVMR) was performed in subsequent analyses. RESULTS: We found that 194, 111, and 69 metabolites were epidemiologically associated (P < 0.001) with CAD, PAD, and VTE, respectively. Metabolomic profiles exhibited variable similarity between disease pairs: CAD and PAD (N = 100 shared associations, R(2) = 0.499), CAD and VTE (N = 68, R(2) = 0.455), and PAD and VTE (N = 54, R(2) = 0.752). MR revealed 28 metabolites that increased risk for both CAD and PAD and 2 metabolites that increased risk for CAD but decreased risk for VTE. Despite strong epidemiologic overlap, no metabolites had a shared genetic relationship between PAD and VTE. MVMR revealed several metabolites with shared causal effects on CAD and PAD related to cholesterol content within very-low-density lipoprotein particles. CONCLUSIONS: While common arterial and venous conditions are associated with overlapping metabolomic profiles, MR prioritized the role of remnant cholesterol in arterial diseases but not venous thrombosis. |
format | Online Article Text |
id | pubmed-10327201 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-103272012023-07-08 Integrative metabolomics differentiate coronary artery disease, peripheral artery disease, and venous thromboembolism risks Lee, Jiwoo Gilliland, Thomas Koyama, Satoshi Nakao, Tetsushi Dron, Jacqueline Lannery, Kim Wong, Megan Peloso, Gina M. Hornsby, Whitney Natarajan, Pradeep medRxiv Article RATIONALE: Arterial and venous cardiovascular conditions, such as coronary artery disease (CAD), peripheral artery disease (PAD), and venous thromboembolism (VTE), are genetically correlated. Interrogating distinct and overlapping mechanisms may shed new light on disease mechanisms. OBJECTIVE: In this study, we aimed to: identify and compare (1) epidemiologic and (2) causal, genetic relationships between metabolites and CAD, PAD, and VTE. METHODS: We used metabolomic data from 95,402 individuals in the UK Biobank, excluding individuals with prevalent cardiovascular disease. Logistic regression models adjusted for age, sex, genotyping array, first five principal components of ancestry, and statin use estimated the epidemiologic associations of 249 metabolites with incident CAD, PAD, or VTE. Bidirectional two-sample Mendelian randomization (MR) estimated the causal effects between metabolites and cardiovascular phenotypes using genome-wide association summary statistics for metabolites (N = 118,466 from UK Biobank), CAD (N = 184,305 from CARDIoGRAMplusC4D 2015), PAD (N = 243,060 from Million Veterans Project) and VTE (N = 650,119 from Million Veterans Project). Multivariable MR (MVMR) was performed in subsequent analyses. RESULTS: We found that 194, 111, and 69 metabolites were epidemiologically associated (P < 0.001) with CAD, PAD, and VTE, respectively. Metabolomic profiles exhibited variable similarity between disease pairs: CAD and PAD (N = 100 shared associations, R(2) = 0.499), CAD and VTE (N = 68, R(2) = 0.455), and PAD and VTE (N = 54, R(2) = 0.752). MR revealed 28 metabolites that increased risk for both CAD and PAD and 2 metabolites that increased risk for CAD but decreased risk for VTE. Despite strong epidemiologic overlap, no metabolites had a shared genetic relationship between PAD and VTE. MVMR revealed several metabolites with shared causal effects on CAD and PAD related to cholesterol content within very-low-density lipoprotein particles. CONCLUSIONS: While common arterial and venous conditions are associated with overlapping metabolomic profiles, MR prioritized the role of remnant cholesterol in arterial diseases but not venous thrombosis. Cold Spring Harbor Laboratory 2023-06-27 /pmc/articles/PMC10327201/ /pubmed/37425786 http://dx.doi.org/10.1101/2023.06.21.23291103 Text en https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Lee, Jiwoo Gilliland, Thomas Koyama, Satoshi Nakao, Tetsushi Dron, Jacqueline Lannery, Kim Wong, Megan Peloso, Gina M. Hornsby, Whitney Natarajan, Pradeep Integrative metabolomics differentiate coronary artery disease, peripheral artery disease, and venous thromboembolism risks |
title | Integrative metabolomics differentiate coronary artery disease, peripheral artery disease, and venous thromboembolism risks |
title_full | Integrative metabolomics differentiate coronary artery disease, peripheral artery disease, and venous thromboembolism risks |
title_fullStr | Integrative metabolomics differentiate coronary artery disease, peripheral artery disease, and venous thromboembolism risks |
title_full_unstemmed | Integrative metabolomics differentiate coronary artery disease, peripheral artery disease, and venous thromboembolism risks |
title_short | Integrative metabolomics differentiate coronary artery disease, peripheral artery disease, and venous thromboembolism risks |
title_sort | integrative metabolomics differentiate coronary artery disease, peripheral artery disease, and venous thromboembolism risks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10327201/ https://www.ncbi.nlm.nih.gov/pubmed/37425786 http://dx.doi.org/10.1101/2023.06.21.23291103 |
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