Effect of HDL disk and LDL dimer presence on lipoprotein particle number determination and subclassification

High-density and low-density lipoproteins (HDL and LDL) are established analytical targets for diagnosis and risk stratification of numerous chronic diseases. This study investigates potential sources of bias in lipoprotein particle counting (HDL-P and LDL-P), focusing on the most atheroprotective small-HDL and most pro-atherogenic small-LDL. Plasma samples were fractionated using asymmetric-flow field-flow fractionation (AF4), coupled with hydrodynamic size measurement and comprehensive liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of each fraction. Concentration-size profiles were deconvoluted into 10 HDL and 8 LDL Gaussian subspecies. Molecular volume ratios were used to evaluate proposed particle models, providing evidence for the presence of s-HDL disk and s-LDL dimers, as sources of bias in calculated HDL-P and LDL-P when spherical particle geometry is assumed. Matching apoA1/HDL-P and apoB/LDL-P to consensus values enabled correction of mass diameters (k*d<sub>m</sub>), with k≈1.2 for s-HDL disks, and k≈0.8 for s-LDL dimers. These corrections resulted in closer agreements of the calculated HDL-P and LDL-P values with those reported by nuclear magnetic resonance spectroscopy (n = 666). After corrections, average AF4-LC-MS/MS versus NMR differences decreased from 20 to 4.9% for HDL-P and from -47% to -5.7% for LDL-P; x-y correlations improved from 0.83 to 0.85 and 0.51 to 1.03, respectively; and both platforms showed a dominant presence of s-HDL and s-LDL subclasses. Overall, the results support standardization of clinical methodologies for lipoprotein subclass measurement around apoA1 and apoB, and harmonization of HDL and LDL subclass definitions based on composition and structural characteristics rather than strictly enforced size cutoffs.

Authors

Institutions

Publication Details

Journal
Analytical and Bioanalytical Chemistry
Published
2026-02-27
DOI
https://doi.org/10.1007/s00216-026-06390-9
Primary Topic
Diabetes, Cardiovascular Risks, and Lipoproteins
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effect of HDL disk and LDL dimer presence on lipoprotein particle number determination and subclassification

Bryan A. Parks, Michael S. Gardner, David Schieltz, Wanda I. Santana et al.
Analytical and Bioanalytical Chemistry
Diabetes, Cardiovascular Risks, and Lipoproteins
article

Effect of HDL disk and LDL dimer presence on lipoprotein particle number determination and subclassification

Bryan A. Parks, Michael S. Gardner, David Schieltz, Wanda I. Santana, Eric C. Leszczynski, Robert W. McGarrah, Paula G. Miller, Jeffrey I. Jones, Jon C. Rees, Kevin Bierbaum, Antony Lehtikoski, Zsuzsanna Kuklenyik, Jack A. Sultan, Christopher Toth, Mark A. Sarzynski, Anna A. Ivanova, Michael F. Andrews, Jennifer D. Kusovschi, John R. Barr, Victoria Connor, Lauren E. Drinkard
article en

Abstract

High-density and low-density lipoproteins (HDL and LDL) are established analytical targets for diagnosis and risk stratification of numerous chronic diseases. This study investigates potential sources of bias in lipoprotein particle counting (HDL-P and LDL-P), focusing on the most atheroprotective small-HDL and most pro-atherogenic small-LDL. Plasma samples were fractionated using asymmetric-flow field-flow fractionation (AF4), coupled with hydrodynamic size measurement and comprehensive liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of each fraction. Concentration-size profiles were deconvoluted into 10 HDL and 8 LDL Gaussian subspecies. Molecular volume ratios were used to evaluate proposed particle models, providing evidence for the presence of s-HDL disk and s-LDL dimers, as sources of bias in calculated HDL-P and LDL-P when spherical particle geometry is assumed. Matching apoA1/HDL-P and apoB/LDL-P to consensus values enabled correction of mass diameters (k*d<sub>m</sub>), with k≈1.2 for s-HDL disks, and k≈0.8 for s-LDL dimers. These corrections resulted in closer agreements of the calculated HDL-P and LDL-P values with those reported by nuclear magnetic resonance spectroscopy (n = 666). After corrections, average AF4-LC-MS/MS versus NMR differences decreased from 20 to 4.9% for HDL-P and from -47% to -5.7% for LDL-P; x-y correlations improved from 0.83 to 0.85 and 0.51 to 1.03, respectively; and both platforms showed a dominant presence of s-HDL and s-LDL subclasses. Overall, the results support standardization of clinical methodologies for lipoprotein subclass measurement around apoA1 and apoB, and harmonization of HDL and LDL subclass definitions based on composition and structural characteristics rather than strictly enforced size cutoffs.

Analytical and Bioanalytical Chemistry
Centers for Disease Control and Prevention (US), University of South Carolina (US), Duke University (US)
Centers for Disease Control and Prevention
Openalex Percentile: Top 42%
Diabetes, Cardiovascular Risks, and Lipoproteins
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.