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Lipoprotein Subclasses Independently Contribute to Subclinical Variance of Microvascular and Macrovascular Health
Lukas Streese1, Hansjörg Habisch2, Arne Deiseroth1
1Department of Sport, Exercise and Health, Medical Faculty, University of Basel, 4052 Basel, Switzerland.
Insights
Lipoprotein subclasses, measured by NMR spectroscopy, better reflect microvascular and macrovascular damage than standard lipids. This offers a more precise way to assess cardiovascular disease risk.
Area of Science:
- Cardiovascular Science
- Biomarker Discovery
- Lipid Metabolism
Background:
- Lipoproteins are established cardiovascular (CV) risk biomarkers.
- Understanding the relationship between lipoprotein subclasses and vascular health is crucial for atherosclerotic CV disease research.
Purpose of the Study:
- To investigate associations between lipoprotein subclasses and microvascular (retinal vessels) and macrovascular (pulse wave velocity) biomarkers.
- To determine if lipoprotein subclasses offer more precise insights into vascular damage compared to traditional lipid measures.
Main Methods:
- Serum samples from 158 participants (EXAMIN AGE study) were analyzed using nuclear magnetic resonance (NMR) spectroscopy.
- Microvascular health assessed via retinal arteriolar and venular diameters.
- Macrovascular health assessed via carotid-to-femoral pulse wave velocity (PWV).
Main Results:
- Nineteen lipoprotein subclasses significantly associated with retinal vessel diameters; nine associated with PWV.
- Lipoprotein subclasses explained up to 26% of microvascular and 12% of macrovascular variation.
- Traditional lipids (HDL-C, LDL-C, triglycerides) explained less variation (13% microvascular, 8% macrovascular).
Conclusions:
- Lipoprotein subclasses provide a more precise reflection of micro- and macrovascular end-organ damage than standard lipid profiles.
- Further research is needed to explore the utility of lipoprotein subclass quantification for CV risk stratification and prediction.
Abstract:
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 (R2 = 0.26, F(29,121) = 2.80, p < 0.001) in micro- and 12% (R2 = 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% (R2 = 0.13, F(3143) = 8.42, p < 0.001) of micro- and 8% (R2 = 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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