Comparison of Three Methods for LDLC Calculation for Cardiovascular Disease Risk Categorisation in Three Distinct Patient Populations.

BACKGROUND: Limitations of the Friedewald equation for low-density-lipoprotein cholesterol (F-LDLC) calculation led to the Martin-Hopkins (M-LDLC) and Sampson-National Institutes of Health (S-LDLC) equations. We studied these newer calculations of LDLC for correlation and discordance for stratification into the Canadian Cardiovascular Society (CCS) 2021 Dyslipidemia Guidelines' cardiovascular disease (CVD) risk categories. METHODS: We performed analyses on lipid profiles from 3 populations: records of a hospital biochemistry laboratory (population 1), lipid clinic patients without select monogenic dyslipidemias (population 2A), and lipid clinic patients with familial hypercholesterolemia (FH; population 2B). RESULTS: There was very strong correlation among the 3 calculated LDLC. In populations 1 and 2A, M-LDLC and S-LDLC were progressively higher than F-LDLC as triglyceride (TG) levels increased from normal to ∼ 5 mmol/L. In population 2B, M-LDLC was higher than F-LDLC, but S-LDLC was progressively lower than F-LDLC. Using the CCS 2021 guidelines' 4 CVD risk categories, 7.0% (population 2A) to 7.2% (population 1) of cases for M-LDLC vs F-LDLC and 3.9% (population 2A) to 4.4% (population 1) of cases for S-LDLC vs F-LDLC were reclassified to an adjacent CVD risk category, mostly from a lower to a higher risk category. CONCLUSIONS: Switching from F-LDLC to S-LDLC or M-LDLC can reclassify up to ∼ 4.4% or 7.2% of patients, respectively, to another CCS CVD risk category. The difference between F-LDLC and M-LDLC or S-LDLC is greater with higher TG, and with lower LDLC. We recommend that clinical laboratories switch to reporting results from either M-LDLC or S-LDLC, but S-LDLC should not be used in FH patients, pending further studies.

A More Atherogenic Lipoprotein Status Is Present in Adults With Type 2 Diabetes Mellitus Than in Those Without With Equivalent Degrees of Hypertriglyceridemia.

OBJECTIVES: The impact of type 2 diabetes (T2DM) on biomarkers denoting lipoprotein compositional status was studied in mild and moderate hypertriglyceridemia (HTG). Diabetic dyslipidemia pathophysiology could contribute to differences in lipoprotein compositional status, which could be reflected in the preferred cardiovascular disease risk prediction markers in HTG: non-high-density lipoprotein cholesterol (non-HDLC) and apolipoprotein B (apoB). METHODS: A total of 2,775 fasting lipid profiles from a tertiary care lipid clinic were analyzed as 2 subgroups (with and without T2DM), stratified by triglyceride (TG) levels: normotriglyceridemia (TG 0.01 to 1.7 mmol/L), mild HTG (TG 1.71 to 5 mmol/L) and moderate HTG (TG 5.01 to 10 mmol/L). The mean non-HDLC:apoB ratio in each TG stratum and subgroup was analyzed. We also used linear regression to assess the correlation between non-HDLC and apoB. RESULTS: The mean non-HDLC:apoB ratio was increased in both subgroups in patients with mild and moderate HTG, compared to those with normotriglyceridemia. In moderate HTG, the mean non-HDLC:apoB ratio in the subgroup with T2DM was significantly lower than the subgroup without T2DM. In mild and moderate HTG, the subgroup with T2DM had a stronger correlation between non-HDLC and apoB than did the subgroup without T2DM. DISCUSSION AND CONCLUSIONS: In mild and moderate HTG, adults with T2DM exhibit lipid profiles that represent a different and more atherogenic lipoprotein compositional status, when compared with adults without T2DM. For the same severity of HTG, the lipoprotein compositional status in diabetic dyslipidemia suggests that there is increased abundance of smaller non-HDL particles and their remnants, which are highly atherogenic.

Relative effect of hypertriglyceridemia on non-HDLC and apolipoprotein B as cardiovascular disease risk markers.

BACKGROUND: Non-high density lipoprotein cholesterol (non-HDLC) represents the cholesterol in triglyceride-rich lipoproteins (TRL) and low-density lipoproteins (LDL). Apolipoprotein B (apoB) reflects the number of TRL and LDL particles. In hypertriglyceridemia (HTG), there is triglyceride (TG) enrichment of TRLs, and also a substantial increase of cholesterol in larger TRLs that considerably augments the non-HDLC value. Therefore, in HTG, non-HDLC could increase disproportionately with respect to apoB. OBJECTIVE: We aimed to compare the relative effect of the full range of mild, moderate, and severe HTG on the status of non-HDLC and apoB as cardiovascular disease (CVD) risk markers. METHODS: Analysis of lipid profile data from 4347 patients in a Lipid Clinic cohort with baseline fasting lipid profiles documented prior to starting lipid-lowering medications. The correlation between non-HDLC and apoB was assessed in intervals of increasing TG. Non-HDLC and apoB were analyzed at each TG level using comparative CVD risk equivalent categories and assessed for divergence and discordance. RESULTS: With increasing TG levels: (1) the correlation between non-HDLC and apoB diminished progressively, (2) non-HDLC levels increased continuously, whereas apoB levels plateaued after an initial increase up to TG of ~ 4.0-5.0 mmol/L (~354-443 mg/dL), (3) there was divergence in the stratification of non-HDLC and apoB into CVD risk equivalent categories. CONCLUSIONS: Non-HDLC and apoB should not be viewed as interchangeable CVD risk markers in the presence of severe HTG. This has never been tested. With increasing HTG severity, discordance between non-HDLC and apoB can cause clinically important divergence in CVD risk categorization.

Calculated Non-HDL Cholesterol Includes Cholesterol in Larger Triglyceride-Rich Lipoproteins in Hypertriglyceridemia.

CONTEXT: Calculated non-high-density lipoprotein (HDL) cholesterol (non-HDLC) should selectively include cholesterol from atherogenic lipoproteins to be a reliable risk marker of cardiovascular disease. In hypertriglyceridemia (HTG), there is increased abundance of larger and less atherogenic triglyceride-rich lipoproteins (TRL), namely, larger very-low-density lipoproteins (VLDL), and chylomicrons. OBJECTIVE: We aim to demonstrate that serum triglyceride (TG) level has a substantial impact on non-HDLC's ability to represent cholesterol from atherogenic lipoproteins, even though TG is not part of the calculation for non-HDLC. DESIGN: Analysis of lipid profile data. SETTINGS: Lipid Clinic patient cohort, and Biochemistry Laboratory patient cohort. PATIENTS OR OTHER PARTICIPANTS: 7,492 patients in the Lipid Clinic cohort with baseline lipid profiles documented prior to starting lipid-lowering medications and 156,311 lipid profiles from The Ottawa Hospital Biochemistry Laboratory cohort. INTERVENTION: None. MAIN OUTCOME MEASURE: Our modeling process includes derivation of TG-interval-specific lipoprotein composition factor (LCF) for TRL, which represents the mass ratio of cholesterol to TG in TRL. A high LCF indicates that the TRLs are mainly the cholesterol-rich atherogenic remnant lipoproteins. A low LCF indicates that the TRLs are mainly the TG-rich larger VLDL and chylomicrons. RESULTS: As serum TG increases, there is progressive decline in the LCF for TRL, which indicates that the calculated non-HDLC level reflects progressive inclusion of cholesterol from larger TRL. This is shown in both cohorts. CONCLUSIONS: Calculated non-HDLC is influenced by TG level. As TG increases, non-HDLC gradually includes more cholesterol from larger TRL, which are less atherogenic than LDL and remnant lipoproteins.