DIRECT MEASUREMENT OF LIPOPROTEIN PARTICLE HETEROGENEITY USING CDMS

Significance of the Topic

Lipoprotein particles (HDL, LDL, Lp(a)) are central to lipid transport and are increasingly implicated in cardiometabolic disease, inflammation, neurodegeneration and host responses to infection. Their biological roles depend on particle-level properties (size, composition, surface charge) that are obscured by ensemble or bulk assays. Direct, single-particle measurements are therefore essential to connect physicochemical heterogeneity with function, disease associations and therapeutic mechanisms.

Objectives and Study Overview

This study applied charge detection mass spectrometry (CDMS) to human plasma-derived lipoproteins to:

• Directly measure mass and charge of individual particles across HDL subclasses (small, medium, large), LDL and Lp(a).
• Characterize particle-level heterogeneity and assess whether nominal subclasses represent discrete populations or a continuum.
• Demonstrate CDMS as an analytical platform with potential for mechanistic and translational lipoprotein research.

Methodology

Preparation and fractionation:

• 500 µL human plasma processed by density-based sequential flotation ultracentrifugation in a fixed-angle rotor (TLA-110).
• Ultracentrifugation steps: 100,000 rpm then 58,000 rpm in a Beckman Coulter Optima MAX-TL at 15 °C to obtain fractions with final density ≈ 1.21 g·mL⁻¹.
• Potassium bromide density media removed using Amicon Ultra-4 centrifugal filter units (Millipore) at 4,500 rpm for 8 min in a Sorvall Legend XF centrifuge.

Sample handling and CDMS acquisition:

• Buffer exchange into 20 mM ammonium acetate, pH 7.4 using Slide-A-Lyzer MINI dialysis devices for 15 min at 4 °C.
• Nano-electrospray ionization of prepared fractions into a benchtop Xevo CDMS instrument (Waters).
• CDMS data processing via the CDMS Toolkit in waters_connect software; statistical analysis scripted in Python.
• Mass histograms constructed with identical logarithmic bins spanning 1×10⁷ to 3×10⁸ Da for all samples to permit direct comparison.

Instrumentation Used

• Xevo CDMS benchtop instrument (Waters) with nano-ESI source.
• Beckman Coulter Optima MAX-TL ultracentrifuge with fixed-angle rotor TLA-110.
• Sorvall Legend XF centrifuge (Thermo Fisher Scientific) for centrifugal filtration steps.
• Amicon Ultra-4 centrifugal filter units (Millipore) and Slide-A-Lyzer MINI dialysis devices (Thermo Scientific).
• Data analysis performed with waters_connect/CDMS Toolkit and Python scripting environment.

Main Results and Discussion

Single-particle mass and charge measurements revealed systematic trends and high heterogeneity across lipoprotein subclasses:

• HDL-S (small HDL) showed relatively narrow mass distributions and limited charge dispersion, consistent with the most homogeneous HDL fraction measured.
• HDL-M (medium HDL) exhibited broader mass and charge distributions relative to HDL-S, indicating growing compositional and structural diversity.
• HDL-L (large HDL) displayed substantial mass dispersion and pronounced charge heterogeneity; distributions suggest multiple overlapping subpopulations rather than a single uniform class.
• Lp(a) particles presented extreme heterogeneity in both mass and charge, consistent with known variability in apolipoprotein(a) isoform size and glycosylation patterns.
• Mass vs. charge density maps and overlays demonstrated a progressive shift toward higher mass and wider distributions from HDL-S to HDL-L and Lp(a), supporting a continuum model of lipoprotein subclasses rather than discrete categories.
• Charge information provided an orthogonal dimension likely reporting differences in lipid composition, protein content and post-translational modifications, thereby enhancing particle classification beyond mass alone.

The results emphasize a key limitation of conventional bulk assays, which yield averaged metrics that mask particle-to-particle variability potentially relevant to biological function and disease risk. CDMS directly resolves that variability, enabling detection of subpopulations and compositional trends within nominal fractions.

Benefits and Practical Applications of the Method

Key advantages and potential uses of CDMS for lipoprotein research:

• Single-particle resolution of mass and charge yields high-confidence discrimination of heterogeneous species missed by ensemble techniques.
• Label-free measurements preserve native-like composition and avoid bias from tagging or digestion.
• Applicable to mechanistic studies linking particle heterogeneity to functional assays (e.g., cholesterol efflux, inflammatory signalling).
• Enables biomarker discovery by identifying subpopulations whose presence or abundance associates with disease states.
• Supports translational applications such as diagnostic development, patient stratification and evaluation of therapeutic interventions.

Future Trends and Opportunities for Utilization

Anticipated developments and directions to increase impact of particle-resolved lipoprotein analysis:

1. Throughput and sensitivity improvements to enable larger-cohort and clinical studies.
2. Integration with separation methods (chromatography, field-flow fractionation) to reduce sample complexity and target specific subpopulations.
3. Coupling CDMS with orthogonal structural and compositional analyses (e.g., proteomics, lipidomics, glycomics) to assign biochemical content to measured mass/charge populations.
4. Standardization of sample preparation, reporting and data formats to support inter-laboratory comparability and regulatory translation.
5. Application to personalized medicine: using particle-resolved metrics for risk stratification, monitoring therapy response, or guiding drug development focused on lipoprotein-targeted interventions.

Conclusion

The study demonstrates that CDMS provides a powerful, label-free approach to directly measure mass and charge of individual lipoprotein particles from human plasma. Measurements reveal increasing heterogeneity across HDL subclasses and pronounced variability in Lp(a), supporting a continuum model of lipoprotein populations. By resolving particle-level distributions that bulk assays obscure, CDMS offers a transformative capability for mechanistic research, biomarker discovery and translational applications. The authors note potential for further method development to support clinical studies and higher-throughput workflows.

Authors, Funding and Conflicts

The study authors are affiliated with Waters Corporation and the University of California, Davis. One author (AZM) reported funding from NIH (2R01GM147545) and the Paul G. Allen Foundation. The authors declared no competing financial interest.

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