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Related Experiment Video

Updated: Jun 11, 2026

Cell-free Biochemical Fluorometric Enzymatic Assay for High-throughput Measurement of Lipid Peroxidation in High Density Lipoprotein

Cell-free Biochemical Fluorometric Enzymatic Assay for High-throughput Measurement of Lipid Peroxidation in High Density Lipoprotein

Published on: October 12, 2017

Lipoprotein(a) in Residual Cardiovascular Risk: Measurement Challenges, Assay Standardisation, and Clinical

Yiwen Lu¹, Dongyang Jiang¹, Jinfeng Zhang²

¹School of Clinical Medicine, Shandong Second Medical University, Weifang, People's Republic of China.

International Journal of General Medicine

|June 10, 2026

Summary

Lipoprotein(a) [Lp(a)] measurement complexity hinders clinical use. Harmonized molar reporting and validated assays are crucial for accurate atherosclerotic cardiovascular disease risk assessment and targeted therapies.

Keywords:

Lp(a)analysis apo(a)apoprotein(a)cardiovascular diseases heart disease risk factors lipoprotein(a)

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Last Updated: Jun 11, 2026

Cell-free Biochemical Fluorometric Enzymatic Assay for High-throughput Measurement of Lipid Peroxidation in High Density Lipoprotein

Cell-free Biochemical Fluorometric Enzymatic Assay for High-throughput Measurement of Lipid Peroxidation in High Density Lipoprotein

Published on: October 12, 2017

Area of Science:

Cardiovascular Medicine
Clinical Chemistry
Biochemistry

Background:

Lipoprotein(a) [Lp(a)] is a key genetic risk factor for atherosclerotic cardiovascular disease (ASCVD).
Measurement complexities, including apo(a) variation and assay biases, limit clinical interpretation of Lp(a).

Purpose of the Study:

To review metrological limitations affecting Lp(a) reporting and clinical utility.
To provide recommendations for improving Lp(a) measurement and risk stratification.

Main Methods:

Review of current literature on Lp(a) measurement techniques and challenges.
Analysis of the impact of Lp(a) variability on LDL-C estimation and risk assessment.

Main Results:

Mass-based reporting and fixed conversions between mg/dL and nmol/L are discouraged.
Automated immunoassays are suitable for screening; ELISA and LC-MS/MS are vital for validation and standardization.
High Lp(a) levels can distort calculated LDL-C, impacting risk assessment and treatment response.

Conclusions:

Validated molar reporting (nmol/L) is preferred for Lp(a).
Harmonized molar measurement, ancestry-inclusive validation, and distinguishing Lp(a) particles from free apo(a) are essential.
Improved Lp(a) assessment will enhance ASCVD risk stratification and Lp(a)-targeted therapies.