To the best of our knowledge, this may be the first analysis specifically designed to address the question if high TG are associated with ArSt, where previous reports show contradictory results. Using a randomnly selected large population-based sample, high TG (≥ 1.7 mmol/l) increased the odds of having high CAVI (≥ 9) by 63%, independed of multiple confounding variables as age, gender, MetS components, total cholesterol, and smoking habits. The prevalence of high CAVI was 10.0% and was associated with male gender, higher age, high BP, dysglycemia, abdominal obesity, and total cholesterol, but not related to smoking and low HDL-c.
Consistent with this result, in Japan [23], in 23,257 urban residents, aged 47.1 ± 12.5 years, odds of having a high CAVI (≥ 90th percentile) per 1-standard deviation increment of TG were almost double (OR = 1.9, 95% CI = 1.81–1.99). In this population, a cut-off value of TG 1.05 mmol/l was more sensitive and specific predicting high CAVI (OR = 2.43, 95 CI 2.14–2.75) than the threshold, currently used in clinical practice (1.7 mmol/l) [11, 23]. In China [8], in 16,733 adults from the southern part of the country, aged 18 or older, subjects with high TG (≥ 1.7 mmol/l) and LDL-c below 1.8 mmol/l were 144% times more likely to have high PWV in comparison to subjects with normal TG and low LDL-C (OR = 2.44, 95% CI = 1.61–3.71) [8]. In 14,071 hypertensive patients from Jiangsu and Anhui Provinces of China [9], with the mean age of 64.4 ± 7.4 years, the association between TG and PWV, remained significant even after adjusting the results for gender, age, BMI, fasting blood glucose, smoking, alcohol consumption, BP, medical treatment etc. (β = 0.54, 95% CI = 0.44–0.65, p < 0.001) [9]. In a prospective observational study assessing 1,447 community-based residences from Beijing [24], followed by 4.8 years, baseline TG was strongly correlated with ArSt during the follow-up evaluation (carotid femoral PWV; β = 0.747, 95% CI = 0.394-1.100, p < 0.001 and carotid-radial PWV; β = 0.367, 95% CI = 0.140–0.593, p = 0.002). Moreover, changes in TGs were directly associated with changes in PWV, every standard deviation increase in TG levels between baseline and follow-up was associated with 29% higher risk for increased change in the PWV between baseline and follow-up (OR = 1.296, 95% CI = 1.064–1.580, p = 0.010) [24]. In Spain [15], in 2351 subjects with the mean age of 61.4 ± 7.7, all MetS components, except HDL-c, were associated with CAVI. TG values were significantly and positively related to CAVI using multivariate linear regressions models (r2 = 0.351; p = 0.002) [15].
On the contrary, in 18 countries from Europe [19], assessing 2224 subjects, aged 40 and older, PWV was higher in subjects with MetS compared with those without (9.57 ± 0.06 vs 8.65 ± 0.10; p < 0.001), but CAVI was similar in those two groups (8.34 ± 0.03 vs 8.29 ± 0.04; p = 0.40). In the multivariate analysis, PWV was positively correlated with age, BP, glucose and HDL-c, but not with waist circumference and TG; CAVI was positively correlated with age, gender, BP, glucose, but not with TG and HDL, and negatively correlated with waist circumference. Authors don’t provide a clear explanation with contradictory results relating waist circumference and CAVI [19]. In a prospective evaluation of 2106 middle aged subjects with MetS from Lithuania [17]. high CAVI values at the baseline was related with higher risk for CVD events after around four years. At the baseline, high CAVI values were related to worse cardiometabolic profile, but not with TG value (p = 0.891) [17]. In Korea, in 1144 adults, older than 18 years from Gyeonggi [12], assessing the association between MetS and CAVI reported that CAVI was independently related with age, sex, diastolic BP, and uric acid, but not with waist circumference, plasma glucose, HDL-c, and TG [12], In two Chinese population studies [13, 20], TG were significantly correlated with CAVI, but this association disappeared after multiple adjustments.
Discrepancies between results of the studies might be partially explained by the differences in the population sample sizes, inclusion criteria for the subject’s recruitment, way of ArSt quantification or the variety of adjustment variables. Studies, performed on large population samples tended to observe positive association between ArSt and TG, however, some of them used PWV as an ArSt marker [8, 9, 24]. Also, studies that failed to find an association between TG and ArSt, were often conducted on the population samples with MetS [17, 19] or diabetes [18], meanwhile studies that are indicating positive relationship included mostly healthy subjects [9, 22, 25]. More prospective studies are needed, in order to clarify the risk of elevated TG and it’s effect on the arterial wall state.
The whole spectrum of possible underlying pathophysiological mechanisms of the influence of lipid profile on ArSt has not been well established yet. However, abnormal lipid profile simultaneously influences several pathways – development of atherosclerotic plaques, oxidative stress, inflammation enhancement, endothelial dysfunction and low availability of nitric oxide [33]. From the point of view of atherosclerosis and CVD, there are four main mechanisms which can indirectly increase CVD risk. First, hydrolysis of postprandial chylomicrons or endogenously formed VLDL leads to further formation of cholesterol-rich remnants, which can enter the subendothelial space through the scavenger receptors and promote formation of the foam-cells [23]. Second, higher Apolipoprotein (Apo) CIII might also have an impact on the metabolism of TGs, through inhibition of TG hydrolysis and increased formation of dense, oxidation-prone low density lipoprotein particles [9, 34]. Liver fat mass was also directly associated with the amount of secreted very low density lipoprotein [34]. Third, high TG might disrupt the mechanism of reverse cholesterol transport [34]. Fourth, in vitro analysis indicates that high TG might also stimulate expression of endothelial mediators, such as endothelin-1, promoting endothelial dysfunction [23].
The main limitation of the present report is that the cross-sectional design doesn’t allow to establish causality between TG and ArSt. Independent association between TG and CAVI as continuous variables was not reported, because the assumptions of linear regression analysis were not met. The future prospective results of this study will allow us to examine the predictive value of lipid profiles on ArSt.