Effects of weight change on apolipoprotein B-containing emerging atherosclerotic cardiovascular disease (ASCVD) risk factors

Obesity, dyslipidemia, and cardiovascular disease: A joint expert review from the Obesity Medicine Association and the National Lipid Association 2024

Background

This joint expert review by the Obesity Medicine Association (OMA) and National Lipid Association (NLA) provides clinicians an overview of the pathophysiologic and clinical considerations regarding obesity, dyslipidemia, and cardiovascular disease (CVD) risk.

Methods

This joint expert review is based upon scientific evidence, clinical perspectives of the authors, and peer review by the OMA and NLA leadership.

Results

Among individuals with obesity, adipose tissue may store over 50% of the total body free cholesterol. Triglycerides may represent up to 99% of lipid species in adipose tissue. The potential for adipose tissue expansion accounts for the greatest weight variance among most individuals, with percent body fat ranging from less than 5% to over 60%. While population studies suggest a modest increase in blood low-density lipoprotein cholesterol (LDL-C) levels with excess adiposity, the adiposopathic dyslipidemia pattern most often described with an increase in adiposity includes elevated triglycerides, reduced high density lipoprotein cholesterol (HDL-C), increased non-HDL-C, elevated apolipoprotein B, increased LDL particle concentration, and increased small, dense LDL particles.

Conclusions

Obesity increases CVD risk, at least partially due to promotion of an adiposopathic, atherogenic lipid profile. Obesity also worsens other cardiometabolic risk factors. Among patients with obesity, interventions that reduce body weight and improve CVD outcomes are generally associated with improved lipid levels. Given the modest improvement in blood LDL-C with weight reduction in patients with overweight or obesity, early interventions to treat both excess adiposity and elevated atherogenic cholesterol (LDL-C and/or non-HDL-C) levels represent priorities in reducing the risk of CVD.

Obesity, dyslipidemia, and cardiovascular disease: A joint expert review from the Obesity Medicine Association and the National Lipid Association 2024

BACKGROUND

This joint expert review by the Obesity Medicine Association (OMA) and National Lipid Association (NLA) provides clinicians an overview of the pathophysiologic and clinical considerations regarding obesity, dyslipidemia, and cardiovascular disease (CVD) risk.

METHODS

This joint expert review is based upon scientific evidence, clinical perspectives of the authors, and peer review by the OMA and NLA leadership.

RESULTS

Among individuals with obesity, adipose tissue may store over 50% of the total body free cholesterol. Triglycerides may represent up to 99% of lipid species in adipose tissue. The potential for adipose tissue expansion accounts for the greatest weight variance among most individuals, with percent body fat ranging from less than 5% to over 60%. While population studies suggest a modest increase in blood low-density lipoprotein cholesterol (LDL-C) levels with excess adiposity, the adiposopathic dyslipidemia pattern most often described with an increase in adiposity includes elevated triglycerides, reduced high-density lipoprotein cholesterol (HDL-C), increased non-HDL-C, elevated apolipoprotein B, increased LDL particle concentration, and increased small, dense LDL particles.

CONCLUSIONS

Obesity increases CVD risk, at least partially due to promotion of an adiposopathic, atherogenic lipid profile. Obesity also worsens other cardiometabolic risk factors. Among patients with obesity, interventions that reduce body weight and improve CVD outcomes are generally associated with improved lipid levels. Given the modest improvement in blood LDL-C with weight reduction in patients with overweight or obesity, early interventions to treat both excess adiposity and elevated atherogenic cholesterol (LDL-C and/or non-HDL-C) levels represent priorities in reducing the risk of CVD.

Rapid, Digital Dietary Assessment in Association with Cardiometabolic Biomarkers

PURPOSE

To examine the associations between dietary intake as assessed by a rapid, image-based digital tool and biomarkers of cardiometabolic health.

DESIGN

Retrospective analysis of adults with blood biomarkers performed by Boston Heart Diagnostics (BHD) between December 2020 and March 2022.

SETTING

Outpatient centers serviced by BHD.

SUBJECTS

546 adults, excluding those taking relevant medications and/or supplements known to affect blood test results.

MEASURES

Laboratory assays of blood specimens were performed by Boston Heart Diagnostics. Nutrient intake and diet quality data were obtained using Diet Quality Photo Navigation (DQPN®; US Patent #11,328,810 B2) technique via Diet ID™ tool.

ANALYSIS

Pearson correlation coefficients (for continuous variables) and Spearman coefficients (for ordinal variables) were used to evaluate associations between nutrient intake data and laboratory data for the full study sample. Two-sided P-values < .05 were considered statistically significant.

RESULTS

Both continuous and ordinal measures of diet quality correlated significantly with HDL-C and triglycerides (n = 485; P < .0 01); with hs-CRP (n = 441; P < .001); with HgbA1c (n = 345; P < .01); with fasting insulin (n = 372; P < .001); and with HOMA-IR (n = 319; P < .001).

CONCLUSION

Findings affirm that rapid, digital diet quality and composition assessment by pattern recognition rather than recall tracks significantly with key biomarkers of cardiometabolic health.

Association of pro-inflammatory cytokines, inflammatory proteins with atherosclerosis index in obese male subjects

OBJECTIVES

Investigation the association of pro-inflammatory markers interleukin (IL)-1β and IL- 10 expression, serum levels of C-reactive protein (CRP), cyclooxygenase-2 (COX2), High-density lipoprotein (HDL), Apolipoprotein A1 (ApoA1), and ATP Binding Cassette Subfamily A Member 1 (ABCA1) inflammatory proteins with atherosclerosis index (homocysteine) in normal-weight and obese male subjects.

METHODS

59 males including 30 obese (Body mass index (BMI) of ≥30 kg/m²) and 29 normal-weight (BMI of 18.5-24.9 kg/m²) were joined to this study. Plasma levels of IL-1β and IL-10 (pg/mL), CRP (pg/mL), COX-2 (ng/mL), APOA1 (mg/dL), ABCA1 (ng/mL), HDL, Cholesterol, and Triglyceride (TG) (mg/dL), and homocysteine (µmol/L) was measured. Association of these biomarkers with homocysteine was determined.

RESULTS

Obese subjects had higher serum levels of IL10, IL1β, CRP, COX-2, TG, and cholesterol concentrations (all p<0.05 except IL-10 and cholesterol) and low levels of HDL, APOA1, and ABCA1 (non-significant differences) in comparison to normal-weight group. Homocysteine levels were high in obese men with no significant differences between the two groups. In obese subjects, homocysteine had a significant inverse correlation with APOA1, ABCA1, and HDL, and a strong and moderate positive correlation was found with CRP and TG levels, respectively.

CONCLUSIONS

High level of homocysteine and its correlation with inflammation proteins and markers in obese subjects appear to be contributed with atherosclerosis development.

Relationship between subclasses low-density lipoprotein and carotid plaque

Backgound

Low-density lipoprotein (LDL) cholesterol can lead to the occurrence of atherosclerotic plaques, but patients with normal LDL still have atherosclerotic plaques in clinical practice. With the proposal of LDL subclass, this experiment investigated the relationship between the LDL content of different subclasses and the stability of carotid plaques.

Methods

Plaque stability was suggested by carotid ultrasound results. 37 patients with stable plaques were classified into one group and 41 patients with unstable plaques were classified into another group. The data of age, glycosylated hemoglobin (Ghb), and homocysteine (Hcy) were collected. The contents of LDL subclasses were measured by LIPOPRINT system. The data of total cholesterol (TC), LDL cholesterol, and triglyceride (TG) were collected. The plaque stability was assessed by carotid artery color Doppler ultrasound and the intima-media thickness (IMT) was measured.

Results

The levels of LDL-1 subclass 19.00 (13.00, 27.50) and LDL-2 subclass (21.62 ± 7.24) in the stable plaque group were higher than those in the unstable plaque group (p < 0.05). The levels of LDL-3 subclass (12.24 ± 4.58), LDL-4 subclass 5.00 (2.00, 9.00), and sd-LDL 0 (0.00, 3.00) in the unstable plaque group were higher than those in the stable plaque group (p < 0.05). LDL-1 subclass (adjusted OR = 0.923 and p < 0.05), and LDL-3 subclass (adjusted OR = 1.176 and p < 0.05) were independent risk factors for plaque stability.

Conclusion

Elevated LDL1 is associated with stable plaques whereas LDL3 was found associated with unstable plaques.

Obesity definition, diagnosis, bias, standard operating procedures (SOPs), and telehealth: An Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) 2022

Background

The Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) regarding definition, diagnosis, bias, standard operating procedures (SOPs) and telehealth is intended to provide clinicians an overview of obesity medicine and provide basic organizational tools towards establishing, directing, managing, and maintaining an obesity medical practice.

Methods

This CPS is based upon published scientific citations, clinical perspectives of OMA authors, and peer review by Obesity Medicine Association leadership.

Results

OMA has defined obesity as: "A chronic, progressive, relapsing, and treatable multi-factorial, neurobehavioral disease, wherein an increase in body fat promotes adipose tissue dysfunction and abnormal fat mass physical forces, resulting in adverse metabolic, biomechanical, and psychosocial health consequences." While body mass index may be sufficiently diagnostic for populations and many patients, accurate diagnosis of adiposity in an individual may require anthropometric assessments beyond body weight alone (e.g., waist circumference, percent body fat, and android/visceral fat). Obesity complications can be categorized as "sick fat disease" (adiposopathy) and/or "fat mass disease." Obesity complications predominantly of fat mass origins include sleep apnea and orthopedic conditions. Obesity complications due to adiposopathic endocrinopathies and/or immunopathies include cardiovascular disease, cancer, elevated blood sugar, elevated blood pressure, dyslipidemia, fatty liver, and alterations in sex hormones in both males (i.e., hypogonadism) and females (i.e., polycystic ovary syndrome). Obesity treatment begins with proactive steps to avoid weight bias, including patient-appropriate language, office equipment, and supplies. To help manage obesity and its complications, this CPS provides a practical template for an obesity medicine practice, creation of standard operating procedures, and incorporation of the OMA "ADAPT" method in telehealth (Assessment, Diagnosis, Advice, Prognosis, and Treatment).

Conclusions

The OMA CPS regarding "Obesity Definition, Diagnosis, Bias, Standard Operating Procedures (SOPs), and Telehealth" is one in a series of OMA CPSs designed to assist clinicians care for patients with the disease of obesity.

The role of adiposity, diet and inflammation on the discordance between LDL-C and apolipoprotein B

BACKGROUND AND AIMS

While low-density lipoprotein cholesterol (LDL-C) is a good predictor of atherosclerotic cardiovascular disease, apolipoprotein B (ApoB) is superior when the two markers are discordant. We aimed to determine the impact of adiposity, diet and inflammation upon ApoB and LDL-C discordance.

METHODS AND RESULTS

Machine learning (ML) and structural equation models (SEMs) were applied to the National Health and Nutrition Examination Survey to investigate cardiometabolic and dietary factors when LDL-C and ApoB are concordant/discordant. Mendelian randomisation (MR) determined whether adiposity and inflammation exposures were causal of elevated/decreased LDL-C and/or ApoB. ML showed body mass index (BMI), dietary saturated fatty acids (SFA), dietary fibre, serum C-reactive protein (CRP) and uric acid were the most strongly associated variables (R² = 0.70) in those with low LDL-C and high ApoB. SEMs revealed that fibre (b = -0.42, p = 0.001) and SFA (b = 0.28, p = 0.014) had a significant association with our outcome (joined effect of ApoB and LDL-C). BMI (b = 0.65, p = 0.001), fibre (b = -0.24, p = 0.014) and SFA (b = 0.26, p = 0.032) had significant associations with CRP. MR analysis showed genetically higher body fat percentage had a significant causal effect on ApoB (Inverse variance weighted (IVW) = Beta: 0.172, p = 0.0001) but not LDL-C (IVW = Beta: 0.006, p = 0.845).

CONCLUSION

Our data show increased discordance between ApoB and LDL-C is associated with cardiometabolic, clinical and dietary abnormalities and that body fat percentage is causal of elevated ApoB.

Apolipoprotein B and Cardiovascular Disease: Biomarker and Potential Therapeutic Target

Apolipoprotein (apo) B, the critical structural protein of the atherogenic lipoproteins, has two major isoforms: apoB48 and apoB100. ApoB48 is found in chylomicrons and chylomicron remnants with one apoB48 molecule per chylomicron particle. Similarly, a single apoB100 molecule is contained per particle of very-low-density lipoprotein (VLDL), intermediate density lipoprotein, LDL and lipoprotein(a). This unique one apoB per particle ratio makes plasma apoB concentration a direct measure of the number of circulating atherogenic lipoproteins. ApoB levels indicate the atherogenic particle concentration independent of the particle cholesterol content, which is variable. While LDL, the major cholesterol-carrying serum lipoprotein, is the primary therapeutic target for management and prevention of atherosclerotic cardiovascular disease, there is strong evidence that apoB is a more accurate indicator of cardiovascular risk than either total cholesterol or LDL cholesterol. This review examines multiple aspects of apoB structure and function, with a focus on the controversy over use of apoB as a therapeutic target in clinical practice. Ongoing coronary artery disease residual risk, despite lipid-lowering treatment, has left patients and clinicians with unsatisfactory options for monitoring cardiovascular health. At the present time, the substitution of apoB for LDL-C in cardiovascular disease prevention guidelines has been deemed unjustified, but discussions continue.

Very Low-Density Lipoprotein Cholesterol May Mediate a Substantial Component of the Effect of Obesity on Myocardial Infarction Risk: The Copenhagen General Population Study

BACKGROUND

Individuals with obesity have higher concentrations of very low-density lipoprotein (VLDL) cholesterol and increased risk of myocardial infarction. We hypothesized that VLDL cholesterol explains a fraction of the excess myocardial infarction risk in individuals with obesity.

METHODS

We included 29 010 individuals free of myocardial infarction at baseline, nested within 109 751 individuals from the Copenhagen General Population Study. During 10 years of follow-up, 2306 individuals developed myocardial infarction. Cholesterol content in large and small VLDLs, in intermediate-density lipoprotein (IDL), and in LDL was measured directly with nuclear magnetic resonance spectroscopy.

RESULTS

Median concentrations of cholesterol in large and small VLDLs were 0.12 mmol/L (interquartile range [IQR], 0.07-0.20 mmol/L; 4.5 mg/dL [IQR, 2.6-6.9 mg/dL]) and 0.6 mmol/L (IQR, 0.5-0.8 mmol/L; 25 mg/dL [IQR, 20-30 mg/dL]) in individuals with obesity vs 0.06 mmol/L (IQR, 0.03-0.1 mmol/L; 2.2 mg/dL [IQR, 1.1-3.8 mg/dL]), and 0.5 mmol/L (IQR, 0.4-0.6 mmol/L; 20 mg/dL (IQR, 16-25 mg/dL]) in individuals with normal weight; in contrast, concentrations of IDL and LDL cholesterol were similar across body mass index (BMI) categories. Cholesterol in large and small VLDLs combined explained 40% (95% CI, 27%-53%) of the excess risk of myocardial infarction associated with higher BMI. In contrast, IDL and LDL cholesterol did not explain excess risk of myocardial infarction, whereas systolic blood pressure explained 17% (11%-23%) and diabetes mellitus explained 8.6% (3.2%-14%).

CONCLUSIONS

VLDL cholesterol explains a large fraction of excess myocardial infarction risk in individuals with obesity. These novel findings support a focus on cholesterol in VLDL for prevention of myocardial infarction and atherosclerotic cardiovascular disease in individuals with obesity.

Elevated Serum Small Dense Low-Density Lipoprotein Cholesterol May Increase the Risk and Severity of Coronary Heart Disease and Predict Cardiovascular Events in Patients with Type 2 Diabetes Mellitus

Background

Coronary heart disease (CHD) is a common and severe complication in type 2 diabetes mellitus (T2DM) patients. Increased amount of circulatory small dense low-density lipoprotein cholesterol (sdLDL-C) particles is known to be a sign of dyslipidemia and can result in atherosclerosis. However, the association between serum sdLDL-C levels and CHD in T2DM patients remains unclear.

Methods

A total of 3684 T2DM patients who received selective coronary angiography (CAG) were selected. For analyzing the association between sdLDL-C and CHD severity in T2DM, the patients with CHD were further divided into four subgroups according to the quartiles of sdLDL-C. A multivariate logistic regression was used for analyzing the risks and severity of CHD. A total of 3427 patients with continuous stable CHD were recruited and followed up for 5 years.

Results

Serum sdLDL-C levels in the CHD group were significantly increased compared with those in the non-CHD group [0.80 (0.49) mmol/L vs. 0.70 (0.30) mmol/L, p < 0.001]. The results from CHD subgroup analysis indicated that the sdLDL-C levels in patients with multiple-vessel disease and high Gensini score (GS) were significantly increased. By adjusting the confounding factors and analyzing with multiple logistic regression, we found that sdLDL-C independently correlated with the presence and severity of CHD (CHD: OR = 2.257; multiple-vessel disease: OR = 3.288; high GS: OR = 2.554). A total of 484 major cardiovascular events (MACEs) were documented. After Kaplan-Meier analysis and chi-squared analysis, the incidence of MACEs in the high sdLDL-C group was higher than that in the low sdLDL-C group (16.04% vs. 12.25%, p = 0.002).

Conclusion

In T2DM patients, elevated serum sdLDL-C may increase the severity of CHD and predict cardiovascular events in the future. Therefore, serum sdLDL-C may be a potential biomarker for the surveillance of CHD in T2DM patients.