Apolipoprotein B is a better marker than non-HDL-cholesterol for the metabolic syndrome in Koreans

Association of apolipoproteins and lipoprotein(a) with metabolic syndrome: a systematic review and meta-analysis

BACKGROUND & AIMS

Apolipoproteins and lipoprotein(a) are associated with various cardiometabolic diseases, including insulin resistance, diabetes mellitus, hypertension, dyslipidemia, among others. This systematic review and meta-analysis was conducted to evaluate the association of these markers with metabolic syndrome (MetS).

METHODS

We ran a systematic search through PubMed, Scopus, Embase, Ovid/Medline, and Web of Science on March 15, 2023. No language or date restrictions were applied. The only synthesised effect measure reported was the odds ratio (OR) with its corresponding 95% confidence interval (95% CI). We utilised the random-effects model for the quantitative synthesis.

RESULTS

We analysed 50 studies (n = 150 519) with different definitions for MetS. Increased ApoB values were associated with MetS (OR = 2.8; 95% CI: 2.44-3.22; p < 0.01, I² = 99%). Decreased ApoA1 values were associated with MetS (OR = 0.42; 95% CI: 0.38-0.47; p < 0.01, I² = 99%). Increased values of the ApoB/ApoA1 ratio were associated with MetS (OR = 4.97; 95% CI: 3.83-6.44; p < 0.01, I² = 97%). Decreased values of Lp(a) were associated with MetS (OR = 0.89; 95% CI: 0.82-0.96; p < 0.01; I² = 92%).

CONCLUSIONS

Increased values of ApoB and ApoB/ApoA1 ratio are associated with MetS, while decreased values of ApoA1 and Lp(a) are associated with MetS. These findings suggest that these lipid markers may serve as potential indicators for identifying subjects at risk of developing MetS. However, further research is required to elucidate the underlying mechanisms of these associations.

Associations of serum apolipoprotein A1, B levels and their ratio with blood pressure in Chinese adults with coronary artery disease

OBJECTIVE

We examined the relationships of apolipoprotein A1 (ApoA1), ApoB levels and ApoB/A1 ratio with blood pressure (BP) in Chinese adults with coronary artery disease (CAD).

METHODS

This cross-sectional study included 4921 adults with CAD. SBP, DBP, serum ApoA1 and ApoB levels were measured. The associations between Apo and BP were assessed by analyses of covariance.

RESULTS

Serum ApoA1 was inversely associated with BP, whereas ApoB and the ApoB/A1 ratio exhibited positive associations with BP. For all subjects, a higher ApoA1 level was associated with lower SBP. Subjects in the fourth quartile for ApoA1 exhibited - 2.85 and - 2.63% lower DBP and mean arterial pressure (MAP), respectively than those in the third quartile. In contrast, higher ApoB and ApoB/A1 ratios were associated with higher SBP, DBP and MAP. The mean differences between ApoB quartiles 4 and 1 were 1.54% for SBP, 2.92% for DBP and 2.29% for MAP. The mean differences between the ApoB/A1 ratio quartiles 4 and 1 were 1.94% for SBP, 3.53% for DBP and 2.80% for MAP. In analyses stratified by gender, graded and inverse associations of ApoA1 with SBP, DBP and MAP were observed in both men and women, but positive associations were observed for ApoB and the ApoB/A1 ratio. Path analysis showed that BMI mediated the associations between ApoB and the ApoB/A1 ratio and SBP.

CONCLUSIONS

In general, serum ApoA1 was inversely associated with BP in persons with CAD. In contrast, serum ApoB and the ApoB/A1 ratio were positively associated with BP, and these associations were mediated by BMI.

Non-high-density lipoprotein fractions are strongly associated with the presence of metabolic syndrome independent of obesity and diabetes: a population-based study among Iranian adults

BACKGROUND

Non-HDL-C as a valuable predictor of premature atherosclerosis, coronary events like first Myocardial infarction and cardiovascular mortality has a high accuracy of measurement both in fasting and non-fasting individuals. Metabolic syndrome (MetS) can promote the development of diabetes mellitus, endothelial dysfunction and atherosclerosis. A common pathway for cross linking of metabolic abnormalities and non-HDL-C has been suggested. In this study we aimed to describe the potential association between non-HDL cholesterol fractions and metabolic syndrome.

METHODS

Data of third national surveillance of the risk factors of non-communicable diseases (SuRFNCD-2007) were analyzed. We defined metabolic syndrome (MetS) according to the Adult Treatment Panel III (ATPIII) and International Diabetes Federation (IDF) criteria for 2125 subjects aging 25-64 years. The receiver operating characteristic (ROC) curves were used to determine the optimal cut-points for the diagnosis of MetS. The curves were depicted for non-high-density lipoprotein cholesterol (non-HDL-C) and difference of total non-HDL-C and LDL-C (Differential cholesterol or Diff-C) as predictors of MetS. Logistic regression was also performed in a complex sample analysis scheme.

RESULTS

The area under the curve (AUC) with 95% Confidence intervals of total non-HDL-C was computed. Values were 0.693 (0.670-0.715) for IDF-defined MetS and 0.719 (0.697-0.740) for ATPIII criteria. The optimal non-HDL-C cut-point we recommend for both criteria is 153.50 mg/dl (sensitivity: 75.7%, specificity: 57.2%, with ATPIII; sensitivity: 73.2%, specificity: 57.1%, with IDF). Using IDF criteria, the accuracy of predictors were greater in non-diabetic subjects. AUC of Diff-C in DM (-) vs. DM (+) were 0.786 (0.765-0.807) vs. 0.627(0.549-0.705). Adults with high non-HDL-C were 4.42 times more likely to have ATPIII-defined MetS (≥190 vs. < 190 mg/dL). Elevated Diff-C corresponded to increased risk of the MetS (ORs: 10.71 and 26.29 for IDF and ATP III criteria, respectively. All P-values <0.001).

CONCLUSIONS

A significant robust association exists between non-HDL-C and MetS whether applying conventional or new thresholds.

Osteoporotic Fracture Risk Assessment Using Bone Mineral Density in Korean: A Community-based Cohort Study

Background

Fracture-risk assessment tool (FRAX) using just clinical risk factors of osteoporosis has been developed to estimate individual risk of osteoporotic fractures. We developed prediction model of fracture risk using bone mineral density (BMD) as well as clinical risk factors in Korean, and assessed the validity of the final model.

Methods

To develop and validate an osteoporotic FRAX, a total of 768 Korean men and women aged 50 to 90 years were followed for 7 years in a community-based cohort study. BMD as well as clinical risk factors for osteoporotic fracture including age, sex, body mass index, history of fragility fracture, family history of fracture, smoking status, alcohol intake, use of oral glucocorticoid, rheumatoid arthritis, and other causes of secondary osteoporosis were assessed biannually.

Results

During the follow-up period, 86 osteoporotic fractures identified (36 in men and 50 in women). The developed prediction models showed high discriminatory power and had goodness of fit.

Conclusions

The developed a Korean specific prediction model for osteoporotic fractures can be easily used as a screening tool to identify individual with high risk of osteoporotic fracture. Further studies for validation are required to confirm the clinical feasibility in general Korean population.

Association of apolipoprotein B and incidence of metabolic syndrome in Korean men: a 5-years' follow-up study

BACKGROUND AND OBJECTIVE

There have been reports for the association between elevated serum apolipoprotein B (ApoB) and several cardiometabolic disorders. However, it remains unclear whether serum ApoB level predicts the development of metabolic syndrome (MetS). Accordingly, we carried out a prospective study to evaluate the longitudinal effects of baseline serum ApoB levels on the development of MetS.

PATIENTS AND METHODS

A cohort of 25,193 healthy Korean men without MetS had been followed up prospectively. Baseline serum ApoB levels were categorized to following quintiles (quintile 1-5: <76.4, 76.4-88.4, 88.4-99.5, 99.5-113.0, ≥113.0). We evaluated the differences in the incidence of MetS according to quintiles of serum ApoB levels. Cox proportional hazards models were used to calculate the adjusted hazard ratios (HRs) for MetS.

RESULTS

During follow-up, 5407 (21.5%) cases developed MetS between 2006 and 2010. Incidence of MetS increased according to quintiles of serum ApoB levels [quintile 1-5: 9.1%, 16.4%, 22.1%, 27.3%, 36.4%, respectively (P for trend <0.001)]. Even after adjusting for various covariates including non-HDL-cholesterol, the hazard ratios (95% CI) for MetS increased in proportion to the quintiles of serum ApoB levels, compared to quintile 1 [quintile 2-5: 1.64 (1.43-1.89), 1.98 (1.71-2.31), 2.32 (1.96-2.75) and 2.92 (2.37-3.60), respectively (P for trend <0.001)]. These associations were apparent still in the clinically relevant subgroup analyses.

CONCLUSIONS

Serum ApoB levels predict MetS, independent of baseline confounding variables including non-HDL-cholesterol.

Apolipoproteins a-I and B as components of metabolic syndrome with respect to diabetes status: a factor analysis

BACKGROUND

The aim of the current study was to elucidate the clustering pattern of metabolic syndrome components along with apolipoproteins (Apo) A-I and B in diabetic and nondiabetic subjects.

METHODS

Factor analysis of conventional variables of metabolic syndrome [i.e., waist circumference, homeostasis model assessment of insulin resistance (HOMA-IR), triglycerides (TG), high-density lipoprotein-cholesterol (HDL-C), and systolic blood pressure (SBP)] with or without addition of Apo A-I and B was performed on 567 and 327 diabetic and nondiabetic subjects, respectively. Thereafter, analyses were repeated after substitution of TG and HDL-C by the TG-to-HDL-C ratio (TG/HDL-C).

RESULTS

Regarding conventional variables of metabolic syndrome, one or two underlying factors were identified, depending on whether lipid measures were entered as two distinct variables or as a composite measure. Apolipoproteins were consistent with a one-factor structure model of metabolic syndrome and did not change the loading pattern remarkably in nondiabetics. TG and HDL-C tended to cluster with Apo B and A-I, respectively, in different models.

CONCLUSION

The current study confirms that addition of Apo A-I and B is consistent with the one-factor model of metabolic syndrome and does not modify the loading pattern remarkably in nondiabetic subjects.

Clinical Impact of Non-High Density Lipoprotein-Cholesterol and Apolipoprotein B on Clinical Outcomes in Metabolic Syndrome Patients With Acute Myocardial Infarction Undergoing Percutaneous Coronary Intervention

Background and Objectives

Subjects and Methods

Results

Conclusion