Excess Triglycerides in Very Low-Density Lipoprotein (VLDL) Estimated from VLDL-Cholesterol could be a Useful Biomarker of Metabolic Dysfunction Associated Steatotic Liver Disease in Patients with Type 2 Diabetes
Year: 2024
Type: article
Study design: Observational Study
Abstract: AIMS: We report that small dense low-density lipoprotein cholesterol (sdLDL-C) levels are sensitive biomarkers of metabolic dysfunction-associated steatotic liver disease (MASLD). Since triglyceride (TG)-rich very low-density lipoprotein (VLDL) is a precursor of sdLDL and is overproduced by MASLD, the composition of VLDL may be more directly associated with MAFLD than sdLDL-C or plasma TG. To identify TG-rich VLDL, this author proposed "Excess TG" and examined its association with MASLD. METHODS: Patients with type 2 diabetes (n=1295), excluding fasting hypertriglyceridemia (TG ≥ 400 mg/dL) and heavy drinkers were examined. Liver steatosis and visceral fat area (VFA) were evaluated using CT. VLDL-C was calculated as the total C minus direct LDL-C minus HDL-C. The average VLDL-TG level can be estimated using VLDL-C×5, according to the principle of the Friedewald equation for LDL-C. Thus, VLDL-TG was estimated as VLDL-C×5, and Excess TG was calculated as plasma TG minus VLDL-C×5. RESULTS: Patients with MASLD were younger, more likely to be men and drinkers, and had higher VFA, TG, sdLDL-C, and excess TG, while VLDL-C was comparable. Excess TG was found to be the most sensitive lipid parameter for identifying MASLD, independent of sdLDL-C, TG, TG/VLDL-C, and VFA. The odds ratios for MASLD were 2.4-, 3.7-, and 3.9-fold higher for Excess TG ranges of 0-24, 25-49, and ≥ 50 mg/dL, respectively, relative to ＜0 mg, and a close relationship remained significant after adjustment for lipid- and adiposity-related parameters. CONCLUSIONS: Excess TG in VLDL was strongly associated with MASLD beyond TG and sdLDL-C levels, which may reflect the presence of TG-rich VLDL.
DOI: 10.5551/jat.65164
Author: Tsutomu Hirano
Institution: Ebina General Hospital
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4402163717