Association of Serum Triglycerides With Arterial Stiffness in Subjects With Low Levels of Low-Density Lipoprotein Cholesterol

Associations between insulin resistance indices and subclinical atherosclerosis: A contemporary review

Even in the absence of hyperglycemia or hyperlipidemia, it has been demonstrated that insulin resistance is an independent risk factor for atherosclerosis. Finding markers of insulin resistance that are associated with markers of atherosclerosis could help identify patients early in their disease course and allow for earlier initiation of preventative treatments. We reviewed available evidence regarding associations between known markers of insulin resistance and known markers of atherosclerosis. Serum triglycerides (TG), triglyceride-glucose index (TyG), and homeostasis model assessment (HOMA) were the insulin resistance markers reviewed. The coronary artery calcium score (CAC), carotid intimal medium thickness (cIMT), and pulse wave velocity (PWV) were reviewed as markers of atherosclerosis. TyG showed the most consistent association with CAC across broad demographic groups, though HOMA showed potential in obese individuals and those without diabetes. The data regarding cIMT and the reviewed insulin resistance markers did not yield any consistent associations, though very elevated TyG did appear to be associated with cIMT among normal weight individuals. Serum triglycerides showed a strong and consistent association with PWV across numerous studies and populations, though TyG index also demonstrated a strong association with PWV in a large systematic review. Of the insulin resistance markers reviewed, the TyG index appears to be most consistently associated with markers of atherosclerosis. TyG can be easily calculated with routine labwork and has the potential to inform decisions regarding early initiation of therapies in patients who would otherwise not be treated. Targeting insulin sensitivity prior to the development of T2DM has the potential to reduce development and progression of atherosclerosis, and patients without T2DM but who have elevated TyG index should be the topic of further research.

Use of Atherogenic Indices as Assessment Methods of Clinical Atherosclerotic Diseases

BACKGROUND

Central illustration : Use of Atherogenic Indices as Assessment Methods of Clinical Atherosclerotic Diseases.

BACKGROUND

The search for clinically useful methods to assess atherosclerotic diseases (ASCVD) with good accuracy, low cost, non-invasiveness, and easy handling has been stimulated for years. Thus, the atherogenic indices evaluated in this study may fit this growing demand.

OBJECTIVES

To assess the potential of atherogenic indices to evaluate patients with clinical atherosclerosis.

METHODS

Single-center cross-sectional study, through which the Castelli I and II indices, the atherogenic index of plasma (AIP), the lipoprotein combine index, and the variation in the peripheral perfusion index between 90 and 120 seconds after an endothelium-dependent (ΔPI90-120) vasodilator stimulus were evaluated in the prediction of atherosclerosis. Statistical significance was set at p < 0.05.

RESULTS

The sample consisted of 298 individuals with an average age of 63.0±16.1 years, of which 57.4% were women. Paired comparisons of the ROC curve analysis of the indices that reached the area under the curve (AUC) > 0.6 show that ΔPI90-120 and AIP were superior to other indices, and no differences were observed between them (difference between AUC = 0.056; 95%CI -0.003-0.115). Furthermore, both the ΔPI90-120 [odds ratio (OR) 9.58; 95%CI 4.71-19.46)] and AIP (OR 5.35; 95%CI 2.30-12.45) were independent predictors of clinical atherosclerosis.

CONCLUSIONS

The AIP and ΔPI90-120 represented better accuracy in discriminating clinical ASCVD. Moreover, they were independent predictors of clinical ASCVD, evidencing a promising possibility for developing preventive and control strategies for cardiovascular diseases. Therefore, they are markers for multicenter studies from the point of view of practicality, low cost, and external validity.

The Impact of the Blood Lipids Levels on Arterial Stiffness

Arterial stiffness is a recognized predictor of cardiovascular morbidity and death. It is an early indicator of arteriosclerosis and is influenced by numerous risk factors and biological processes. The lipid metabolism is crucial and standard blood lipids, non-conventional lipid markers and lipid ratios are associated with arterial stiffness. The objective of this review was to determine which lipid metabolism marker has a greater correlation with vascular aging and arterial stiffness. Triglycerides (TG) are the standard blood lipids that have the strongest associations with arterial stiffness, and are often linked to the early stages of cardiovascular diseases, particularly in patients with low LDL-C levels. Studies often show that lipid ratios perform better overall than any of the individual variables used alone. The relation between arterial stiffness and TG/HDL-C has the strongest evidence. It is the lipid profile of atherogenic dyslipidemia that is found in several chronic cardio-metabolic disorders, and is considered one of the main causes of lipid-dependent residual risk, regardless of LDL-C concentration. Recently, the use of alternative lipid parameters has also been increasing. Both non-HDL and ApoB are very well correlated with arterial stiffness. Remnant cholesterol is also a promising alternative lipid parameter. The findings of this review suggest that the main focus should be on blood lipids and arterial stiffness, especially in individuals with cardio-metabolic disorders and residual cardiovascular risk.

Contribution of metabolic risk factors and lifestyle behaviors to cardiovascular disease: A mendelian randomization study

BACKGROUND AND AIMS

Etiologic associations between some modifiable factors (metabolic risk factors and lifestyle behaviors) and cardiovascular disease (CVD) remain unclear. To identify targets for CVD prevention, we evaluated the causal associations of these factors with coronary artery disease (CAD) and ischemic stroke using a two-sample Mendelian randomization (MR) method.

METHODS AND RESULTS

Previously published genome-wide association studies (GWASs) for blood pressure (BP), glucose, lipids, overweight, smoking, alcohol intake, sedentariness, and education were used to identify instruments for 15 modifiable factors. We extracted effects of the genetic variants used as instruments for the exposures on coronary artery disease (CAD) and ischemic stroke from large GWASs (N = 60 801 cases/123 504 controls for CAD and N = 40 585 cases/406 111 controls for ischemic stroke). Genetically predicted hypertension (CAD: OR, 5.19 [95% CI, 4.21-6.41]; ischemic stroke: OR, 4.92 [4.12-5.86]), systolic BP (CAD: OR, 1.03 [1.03-1.04]; ischemic stroke: OR, 1.03 [1.03-1.03]), diastolic BP (CAD: OR, 1.05 [1.05-1.06]; ischemic stroke: OR, 1.05 [1.04-1.05]), type 2 diabetes (CAD: OR, 1.11 [1.08-1.15]; ischemic stroke: OR, 1.07 [1.04-1.10]), smoking initiation (CAD: OR, 1.26 [1.18-1.35]; ischemic stroke: OR, 1.24 [1.16-1.33]), educational attainment (CAD: OR, 0.62 [0.58-0.66]; ischemic stroke: OR, 0.68 [0.63-0.72]), low-density lipoprotein cholesterol (CAD: OR, 1.55 [1.41-1.71]), high-density lipoprotein cholesterol (CAD: OR, 0.82 [0.74-0.91]), triglycerides (CAD: OR, 1.29 [1.14-1.45]), body mass index (CAD: OR, 1.25 [1.19-1.32]), and alcohol dependence (OR, 1.04 [1.03-1.06]) were causally related to CVD.

CONCLUSION

This systematic MR study identified 11 modifiable factors as causal risk factors for CVD, indicating that these factors are important targets for preventing CVD.

Evaluation of non-invasive arterial stiffness parameters and their relationship with physical activity, anthropometric indices and lipid profiles in healthy middle-aged adults: Results of the PERSIAN cohort study

BACKGROUND

Arterial stiffness (AS) indicates the initial stage of cardiovascular disease (CVD), which is associated with modifiable and lifestyle risk factors. We aimed to examine the association of AS with anthropometric indices, lipid profiles and physical activity (PA).

METHODS

Six hundred and fifty-eight healthy middle-aged adults were selected and anthropometric indices [body mass index, waist circumferences (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), neck circumferences, a body shape index (ABSI), body roundness index (BRI), body fat mass (BFM), visceral fat area, fat-free mass (FFM), lipid profiles and PA] were measured. AS is measured by carotid-femoral pulse wave velocity (cf-PWV) and central augmentation index (cAIx).

RESULTS

Our results show that cf-PWV was positively associated with TGs (β = 0.10, P = .01) and anthropometric indices correlated with WC (β = 0.11, P = .02), WHR (β = 0.09, P = .03), WHtR (β = 0.1, P = .02) and BRI (β = 0.09, P = .04). cAIx was independently positively associated with cholesterol (β = 0.08, P = .03), WC (β = 0.1, P = .03), WHR (β = 0.09, P = .02), ABSI (β = 0.09, P = .01), BRI (β = 0.08, P = .05), visceral fat area (β = 0.09, P = .03) and BFM (β = 0.08, P = .04) and negatively associated with PA (β = -0.08, P = .03).

CONCLUSIONS

WC, WHR and BRI were associated with both cf-PWV and cAIx. TGs and WHtR were associated with cf-PWV, while cAIx was associated with ABSI, improving these indices may be helpful to prevent CVD.

Association of Cardiovascular Risk Factors and Lifestyle Behaviors With Hypertension

Hypertension is a major risk factor for cardiovascular disease and mortality. To identify targets for the prevention of hypertension and its associated disease burden, we used the 2-sample Mendelian randomization method to investigate the causal associations of 18 cardiovascular risk factors and lifestyle behaviors with hypertension. From European-descent genome-wide association studies, we selected genetic variants (P<5×10−8) for type 2 diabetes, fasting glucose, lipids, body mass index, smoking, alcohol and coffee consumption, physical activity, sleep duration, insomnia, and educational level. We extracted the genetic associations with hypertension from 2 European cohorts: the FinnGen Study (15 870 cases and 74 345 controls) and UK Biobank (54 358 cases and 408 652 controls). The inverse-variance weighted method was used as main analysis method. Genetically predicted triglycerides (pooled odds ratio [OR] per 1 SD, 1.17 [1.10–1.25]), body mass index (OR per 1 SD, 1.42 [1.37–1.48]), alcohol dependence (OR, 1.10 [1.06–1.13]), and insomnia (OR, 1.17 [1.13–1.20]) were associated with a higher odds of hypertension. Higher genetically predicted high-density lipoprotein cholesterol (OR per 1 SD, 0.88 [0.83–0.94]) and educational level (OR per 1 SD, 0.56 [0.54–0.59]) were associated with a lower odds of hypertension. Suggestive evidence was obtained for type 2 diabetes, smoking initiation and alcohol consumption with a higher hypertension odds, and longer sleep duration with a lower hypertension odds. This Mendelian randomization study identified high-density lipoprotein cholesterol, triglycerides, body mass index, alcohol dependence, insomnia, and educational level as causal risk factors for hypertension. This implicates that these modifiable risk factors are important targets in the prevention of hypertension.

Atherogenic index of plasma is related to arterial stiffness but not to blood pressure in normotensive and never-treated hypertensive subjects

BACKGROUND AND AIMS

Atherogenic index of plasma (AIP), defined as the logarithm of triglycerides to high-density lipoprotein cholesterol (HDL-C) ratio, is a strong predictor of future cardiovascular disease. Our aim was to examine the association of AIP with haemodynamic variables in normotensive and never-treated hypertensive subjects in a cross-sectional study.

METHODS

Supine haemodynamics in 615 subjects without antihypertensive and lipid-lowering medications were examined using whole-body impedance cardiography and radial pulse wave analysis. Linear regression analysis was applied to investigate the association of AIP with haemodynamic variables and age, sex, body mass index (BMI), smoking status, alcohol consumption, plasma C-reactive protein, electrolytes, uric acid, low density lipoprotein cholesterol (LDL-C), estimated glomerular filtration rate, and quantitative insulin sensitivity check index.

RESULTS

The demographics and laboratory values of the study population were (mean ± 95% confidence interval): age 44.9 ± 1.0 years, BMI 26.8 ± 0.4 kg/m², office blood pressure 140.6 ± 1.6/89.4 ± 1.0 mmHg, total cholesterol 5.2 ± 0.08, LDL-C 3.1 ± 0.08, triglycerides 1.2 ± 0.08, HDL-C 1.6 ± 0.04 mmol/l, and AIP -0.15 ± 0.02. Age (standardized coefficient Beta 0.508, p < .001) and aortic systolic blood pressure (Beta 0.239, p < .001) presented with the strongest associations with pulse wave velocity. However, AIP was also associated with pulse wave velocity (Beta 0.145, p < .001). AIP was not related with aortic or radial blood pressure, cardiac output, systemic vascular resistance, or augmentation index.

CONCLUSIONS

AIP is directly and independently associated with arterial stiffness, a variable strongly related to cardiovascular risk. This supports more widespread use of AIP in standard clinical cardiovascular disease risk evaluation.