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Method for estimating high sdLDL-C by measuring triglyceride and apolipoprotein B levels.
Toshiyuki Hayashi1, Shinji Koba2, Yasuki Ito3
1Department of Medicine, Division of Diabetes, Metabolism, and Endocrinology, Showa University School of Medicine, 1-5-8 Hatanodai, Shinagawa, Tokyo, 142-8666, Japan.
Lipids in Health and Disease
|January 28, 2017
Summary
A new "LDL window" method estimates high small dense low-density lipoprotein cholesterol (sdLDL-C) levels using conventional tests. This approach identifies patients at high risk for coronary artery disease (CAD) independent of LDL-C.
Area of Science:
- Cardiovascular Medicine
- Lipid Metabolism
- Clinical Chemistry
Background:
- Direct measurement of small dense low-density lipoprotein cholesterol (sdLDL-C) is not standard clinical practice.
- A simpler method, the "LDL window," is proposed to estimate high sdLDL-C levels using conventional assays.
Purpose of the Study:
- To develop and validate a simpler method, the "LDL window," for estimating high sdLDL-C levels.
- To assess the utility of the "LDL window" in identifying patients at high risk for coronary artery disease (CAD).
Main Methods:
- Analysis of previous studies (2006-2008) involving healthy subjects, type 2 diabetes, and CAD patients.
- Utilized apolipoprotein B (apoB) for LDL particle number estimation (cutoff: 110 mg/dL) and triglycerides (TGs) for LDL particle size estimation (cutoff: 150 mg/dL).
- An "alternative LDL window" used non-high-density lipoprotein cholesterol (non-HDL-C) (cutoff: 170 mg/dL) and TG.
Main Results:
- The hyper-triglyceridemia/hyper-apolipoprotein B (hyper-TG/hyper-apoB) group in the "LDL window" comprised over 90% of subjects with high sdLDL-C (Q4).
- sdLDL-C levels were significantly higher (50%) in the hyper-TG/hyper-apoB group among patients with diabetes and CAD compared to controls.
- Similar findings were observed using the "alternative LDL window."
Conclusions:
- The proposed "LDL window" method effectively identifies individuals with high sdLDL-C.
- This method can aid in identifying patients at high risk for CAD, independent of standard LDL-C measurements.

