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Lipoprotein Subclasses Independently Contribute to Subclinical Variance of Microvascular and Macrovascular Health

Lipoproteins are important cardiovascular (CV) risk biomarkers. This study aimed to investigate the associations of lipoprotein subclasses with micro- and macrovascular biomarkers to better understand how these subclasses relate to atherosclerotic CV diseases. One hundred and fifty-eight serum sampl...

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Autores principales: Streese, Lukas, Habisch, Hansjörg, Deiseroth, Arne, Carrard, Justin, Infanger, Denis, Schmidt-Trucksäss, Arno, Madl, Tobias, Hanssen, Henner
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9332701/
https://www.ncbi.nlm.nih.gov/pubmed/35897932
http://dx.doi.org/10.3390/molecules27154760
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author Streese, Lukas
Habisch, Hansjörg
Deiseroth, Arne
Carrard, Justin
Infanger, Denis
Schmidt-Trucksäss, Arno
Madl, Tobias
Hanssen, Henner
author_facet Streese, Lukas
Habisch, Hansjörg
Deiseroth, Arne
Carrard, Justin
Infanger, Denis
Schmidt-Trucksäss, Arno
Madl, Tobias
Hanssen, Henner
author_sort Streese, Lukas
collection PubMed
description Lipoproteins are important cardiovascular (CV) risk biomarkers. This study aimed to investigate the associations of lipoprotein subclasses with micro- and macrovascular biomarkers to better understand how these subclasses relate to atherosclerotic CV diseases. One hundred and fifty-eight serum samples from the EXAMIN AGE study, consisting of healthy individuals and CV risk patients, were analysed with nuclear magnetic resonance (NMR) spectroscopy to quantify lipoprotein subclasses. Microvascular health was quantified by measuring retinal arteriolar and venular diameters. Macrovascular health was quantified by measuring carotid-to-femoral pulse wave velocity (PWV). Nineteen lipoprotein subclasses showed statistically significant associations with retinal vessel diameters and nine with PWV. These lipoprotein subclasses together explained up to 26% of variation (R(2) = 0.26, F(29,121) = 2.80, p < 0.001) in micro- and 12% (R(2) = 0.12, F(29,124) = 1.70, p = 0.025) of variation in macrovascular health. High-density (HDL-C) and low-density lipoprotein cholesterol (LDL-C) as well as triglycerides together explained up to 13% (R(2) = 0.13, F(3143) = 8.42, p < 0.001) of micro- and 8% (R(2) = 0.08, F(3145) = 5.46, p = 0.001) of macrovascular variation. Lipoprotein subclasses seem to reflect micro- and macrovascular end organ damage more precisely as compared to only measuring HDL-C, LDL-C and triglycerides. Further studies are needed to analyse how the additional quantification of lipoprotein subclasses can improve CV risk stratification and CV disease prediction.
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spelling pubmed-93327012022-07-29 Lipoprotein Subclasses Independently Contribute to Subclinical Variance of Microvascular and Macrovascular Health Streese, Lukas Habisch, Hansjörg Deiseroth, Arne Carrard, Justin Infanger, Denis Schmidt-Trucksäss, Arno Madl, Tobias Hanssen, Henner Molecules Article Lipoproteins are important cardiovascular (CV) risk biomarkers. This study aimed to investigate the associations of lipoprotein subclasses with micro- and macrovascular biomarkers to better understand how these subclasses relate to atherosclerotic CV diseases. One hundred and fifty-eight serum samples from the EXAMIN AGE study, consisting of healthy individuals and CV risk patients, were analysed with nuclear magnetic resonance (NMR) spectroscopy to quantify lipoprotein subclasses. Microvascular health was quantified by measuring retinal arteriolar and venular diameters. Macrovascular health was quantified by measuring carotid-to-femoral pulse wave velocity (PWV). Nineteen lipoprotein subclasses showed statistically significant associations with retinal vessel diameters and nine with PWV. These lipoprotein subclasses together explained up to 26% of variation (R(2) = 0.26, F(29,121) = 2.80, p < 0.001) in micro- and 12% (R(2) = 0.12, F(29,124) = 1.70, p = 0.025) of variation in macrovascular health. High-density (HDL-C) and low-density lipoprotein cholesterol (LDL-C) as well as triglycerides together explained up to 13% (R(2) = 0.13, F(3143) = 8.42, p < 0.001) of micro- and 8% (R(2) = 0.08, F(3145) = 5.46, p = 0.001) of macrovascular variation. Lipoprotein subclasses seem to reflect micro- and macrovascular end organ damage more precisely as compared to only measuring HDL-C, LDL-C and triglycerides. Further studies are needed to analyse how the additional quantification of lipoprotein subclasses can improve CV risk stratification and CV disease prediction. MDPI 2022-07-25 /pmc/articles/PMC9332701/ /pubmed/35897932 http://dx.doi.org/10.3390/molecules27154760 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Streese, Lukas
Habisch, Hansjörg
Deiseroth, Arne
Carrard, Justin
Infanger, Denis
Schmidt-Trucksäss, Arno
Madl, Tobias
Hanssen, Henner
Lipoprotein Subclasses Independently Contribute to Subclinical Variance of Microvascular and Macrovascular Health
title Lipoprotein Subclasses Independently Contribute to Subclinical Variance of Microvascular and Macrovascular Health
title_full Lipoprotein Subclasses Independently Contribute to Subclinical Variance of Microvascular and Macrovascular Health
title_fullStr Lipoprotein Subclasses Independently Contribute to Subclinical Variance of Microvascular and Macrovascular Health
title_full_unstemmed Lipoprotein Subclasses Independently Contribute to Subclinical Variance of Microvascular and Macrovascular Health
title_short Lipoprotein Subclasses Independently Contribute to Subclinical Variance of Microvascular and Macrovascular Health
title_sort lipoprotein subclasses independently contribute to subclinical variance of microvascular and macrovascular health
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9332701/
https://www.ncbi.nlm.nih.gov/pubmed/35897932
http://dx.doi.org/10.3390/molecules27154760
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