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Metabolomic Profiling of Cholesterol Efflux Capacity in a Multiethnic Population: Insights From MESA

BACKGROUND: Impaired cholesterol efflux capacity (CEC) is a novel lipid metabolism trait associated with atherosclerotic cardiovascular disease. Mechanisms underlying CEC variation are unknown. We evaluated associations of circulating metabolites with CEC to advance understanding of metabolic pathwa...

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Autores principales: Hunter, Wynn G., Smith, Alexander G., Pinto, Rui C., Saldanha, Suzanne, Gangwar, Anamika, Pahlavani, Mandana, Deodhar, Sneha, Wilkins, John, Pandey, Ambarish, Herrington, David, Greenland, Philip, Tzoulaki, Ioanna, Rohatgi, Anand
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10521786/
https://www.ncbi.nlm.nih.gov/pubmed/37615111
http://dx.doi.org/10.1161/ATVBAHA.122.318222
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author Hunter, Wynn G.
Smith, Alexander G.
Pinto, Rui C.
Saldanha, Suzanne
Gangwar, Anamika
Pahlavani, Mandana
Deodhar, Sneha
Wilkins, John
Pandey, Ambarish
Herrington, David
Greenland, Philip
Tzoulaki, Ioanna
Rohatgi, Anand
author_facet Hunter, Wynn G.
Smith, Alexander G.
Pinto, Rui C.
Saldanha, Suzanne
Gangwar, Anamika
Pahlavani, Mandana
Deodhar, Sneha
Wilkins, John
Pandey, Ambarish
Herrington, David
Greenland, Philip
Tzoulaki, Ioanna
Rohatgi, Anand
author_sort Hunter, Wynn G.
collection PubMed
description BACKGROUND: Impaired cholesterol efflux capacity (CEC) is a novel lipid metabolism trait associated with atherosclerotic cardiovascular disease. Mechanisms underlying CEC variation are unknown. We evaluated associations of circulating metabolites with CEC to advance understanding of metabolic pathways involved in cholesterol efflux regulation. METHODS: Participants enrolled in the MESA (Multi-Ethnic Study of Atherosclerosis) who underwent nuclear magnetic resonance metabolome profiling and CEC measurement (N=3543) at baseline were included. Metabolite associations with CEC were evaluated using standard linear regression analyses. Repeated ElasticNet and multilayer perceptron regression were used to assess metabolite profile predictive performance for CEC. Features important for CEC prediction were identified using Shapley Additive Explanations values. RESULTS: Greater CEC was significantly associated with metabolite clusters composed of the largest-sized particle subclasses of VLDL (very-low-density lipoprotein) and HDL (high-density lipoprotein), as well as their constituent apo A(1), apo A(2), phospholipid, and cholesterol components (β=0.072–0.081; P<0.001). Metabolite profiles had poor accuracy for predicting in vitro CEC in linear and nonlinear analyses (R(2)<0.02; Spearman ρ<0.18). The most important feature for CEC prediction was race, with Black participants having significantly lower CEC compared with other races. CONCLUSIONS: We identified independent associations among CEC, the largest-sized particle subclasses of VLDL and HDL, and their constituent apolipoproteins and lipids. A large proportion of variation in CEC remained unexplained by metabolites and traditional clinical risk factors, supporting further investigation into genomic, proteomic, and phospholipidomic determinants of CEC.
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spelling pubmed-105217862023-09-27 Metabolomic Profiling of Cholesterol Efflux Capacity in a Multiethnic Population: Insights From MESA Hunter, Wynn G. Smith, Alexander G. Pinto, Rui C. Saldanha, Suzanne Gangwar, Anamika Pahlavani, Mandana Deodhar, Sneha Wilkins, John Pandey, Ambarish Herrington, David Greenland, Philip Tzoulaki, Ioanna Rohatgi, Anand Arterioscler Thromb Vasc Biol Translational Sciences BACKGROUND: Impaired cholesterol efflux capacity (CEC) is a novel lipid metabolism trait associated with atherosclerotic cardiovascular disease. Mechanisms underlying CEC variation are unknown. We evaluated associations of circulating metabolites with CEC to advance understanding of metabolic pathways involved in cholesterol efflux regulation. METHODS: Participants enrolled in the MESA (Multi-Ethnic Study of Atherosclerosis) who underwent nuclear magnetic resonance metabolome profiling and CEC measurement (N=3543) at baseline were included. Metabolite associations with CEC were evaluated using standard linear regression analyses. Repeated ElasticNet and multilayer perceptron regression were used to assess metabolite profile predictive performance for CEC. Features important for CEC prediction were identified using Shapley Additive Explanations values. RESULTS: Greater CEC was significantly associated with metabolite clusters composed of the largest-sized particle subclasses of VLDL (very-low-density lipoprotein) and HDL (high-density lipoprotein), as well as their constituent apo A(1), apo A(2), phospholipid, and cholesterol components (β=0.072–0.081; P<0.001). Metabolite profiles had poor accuracy for predicting in vitro CEC in linear and nonlinear analyses (R(2)<0.02; Spearman ρ<0.18). The most important feature for CEC prediction was race, with Black participants having significantly lower CEC compared with other races. CONCLUSIONS: We identified independent associations among CEC, the largest-sized particle subclasses of VLDL and HDL, and their constituent apolipoproteins and lipids. A large proportion of variation in CEC remained unexplained by metabolites and traditional clinical risk factors, supporting further investigation into genomic, proteomic, and phospholipidomic determinants of CEC. Lippincott Williams & Wilkins 2023-08-24 2023-10 /pmc/articles/PMC10521786/ /pubmed/37615111 http://dx.doi.org/10.1161/ATVBAHA.122.318222 Text en © 2023 The Authors. https://creativecommons.org/licenses/by-nc-nd/4.0/Arteriosclerosis, Thrombosis, and Vascular Biology is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution Non-Commercial-NoDerivs (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited, the use is noncommercial, and no modifications or adaptations are made.
spellingShingle Translational Sciences
Hunter, Wynn G.
Smith, Alexander G.
Pinto, Rui C.
Saldanha, Suzanne
Gangwar, Anamika
Pahlavani, Mandana
Deodhar, Sneha
Wilkins, John
Pandey, Ambarish
Herrington, David
Greenland, Philip
Tzoulaki, Ioanna
Rohatgi, Anand
Metabolomic Profiling of Cholesterol Efflux Capacity in a Multiethnic Population: Insights From MESA
title Metabolomic Profiling of Cholesterol Efflux Capacity in a Multiethnic Population: Insights From MESA
title_full Metabolomic Profiling of Cholesterol Efflux Capacity in a Multiethnic Population: Insights From MESA
title_fullStr Metabolomic Profiling of Cholesterol Efflux Capacity in a Multiethnic Population: Insights From MESA
title_full_unstemmed Metabolomic Profiling of Cholesterol Efflux Capacity in a Multiethnic Population: Insights From MESA
title_short Metabolomic Profiling of Cholesterol Efflux Capacity in a Multiethnic Population: Insights From MESA
title_sort metabolomic profiling of cholesterol efflux capacity in a multiethnic population: insights from mesa
topic Translational Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10521786/
https://www.ncbi.nlm.nih.gov/pubmed/37615111
http://dx.doi.org/10.1161/ATVBAHA.122.318222
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