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Quantitative Lipoprotein Subclass Analysis in Pig Plasma by 1H NMR Spectroscopy and Stability Assessment
Ran Ma1, Yajie Wang1, Ying Li1
1Department of Food Science and Engineering, College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen 518060, China.
Analytical Chemistry
|March 18, 2025
Summary
This study introduces a novel 1H NMR method for predicting lipoprotein subclasses in pig plasma using partial least-squares regression (PLSR). This stable and accurate method aids in understanding lipoprotein function and mechanisms.
Area of Science:
- Biochemistry
- Analytical Chemistry
- Metabolomics
Background:
- Lipoprotein subclasses play critical roles in lipid metabolism and cardiovascular health.
- Accurate quantification of lipoprotein subclasses is essential for understanding their biological functions.
- Existing methods for lipoprotein analysis can be complex and time-consuming.
Purpose of the Study:
- To develop and validate an optimized 1H NMR-based detection method for accurate prediction of lipoprotein subclasses in pig plasma.
- To establish partial least-squares regression (PLSR) models for quantifying various lipoprotein subclasses.
- To provide a reliable methodological basis for future research on lipoprotein subclasses.
Main Methods:
- Optimization and evaluation of a 1H NMR detection method for plasma metabolites, assessing intraday and interday variability.
- Development of PLSR models combining 1H NMR spectra and ultracentrifugation data to predict 116 lipoprotein subclasses across four major classes (VLDL, LDL, IDL, HDL).
- Validation of PLSR models using cross-validation to assess prediction accuracy (R2 values).
Main Results:
- The optimized 1H NMR method demonstrated high stability and reproducibility (coefficients of variation < 5%).
- PLSR models accurately predicted 107 out of 116 lipoprotein subclasses (R2 > 0.5), meeting method requirements.
- Models for the remaining nine subclasses showed good performance (0.2 < R2 < 0.5), meeting basic requirements.
- Predicted concentrations for key lipoprotein components (APO A1, APO B, PL, TG, CH, FC, CE) were established.
Conclusions:
- A robust and accurate 1H NMR-based method for predicting lipoprotein subclasses in pig plasma was successfully established.
- The developed PLSR models offer a reliable tool for quantitative analysis of lipoprotein subclasses.
- This methodology provides a foundation for investigating the molecular mechanisms, functions, and applications of lipoprotein subclasses.
