Association Between Nontraditional Lipid Profiles and Peripheral Arterial Disease in Chinese adults with Hypertension

doi:10.21203/rs.3.rs-55449/v1

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Association Between Nontraditional Lipid Profiles and Peripheral Arterial Disease in Chinese adults with Hypertension

https://doi.org/10.21203/rs.3.rs-55449/v1

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published 03 Nov, 2020

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Background: Data concerning the association between nontraditional lipid profiles [total cholesterol (TC)/high-density lipoprotein cholesterol (HDL-C) ratio, triglyceride (TG)/HDL-C ratio, low-density lipoprotein cholesterol (LDL-C)/HDL-C ratio, non-high-density lipoprotein cholesterol (non-HDL-C)] and the risk of peripheral artery disease (PAD) are limited. We aimed to evaluate the association between nontraditional lipid indices and the risk of PAD in Chinese hypertensive population.

Methods: In the cross-sectional study, a total of 10,900 adults with hypertension were enrolled. PAD was defined as ankle-brachial index < 0.9. Multivariate logistic regression analysis was performed to examine the association between nontraditional lipid profiles and PAD. Receiver operating characteristic analysis was also used.

Results: All nontraditional lipid profiles were independently and positively associated with the prevalence of PAD in a dose response fashion. In multivariable models, we observed a 37%, 14%, 40%, and 24% higher risk for PAD with each SD increment in TC/HDL-C, TG/HDL-C, LDL-C/HDL-C ratios, and non-HDL-C levels, respectively. Compared with the lowest tertile, the multivariate-adjusted ORs (95% CI) were 1.77 (1.31, 2.40), 1.71 (1.25, 2.34), 2.03 (1.50, 2.74), 1.70 (1.25, 2.31) for the highest tertile of TC/HDL-C, TG/HDL-C, LDL-C/HDL-C ratios, and non-HDL-C, respectively. Furthermore, the area under the curves (AUCs) for LDL-C/HDL-C ratio (0.548; 95% CI, 0.516-0.581) and TC/HDL-C ratio (0.547; 95% CI, 0.514-0.579) were significantly larger than those for TG/HDL-C ratio (0.508; 95% CI, 0.461-0.523) and non-HDL-C (0.519; 95% CI, 0.486-0.552).

Conclusions: All nontraditional lipid profiles were positively associated with PAD in Chinese adults with hypertension, among which LDL-C/HDL-C and TC/HDL-C ratio were better for predicting PAD.

Trial registration: CHiCTR, ChiCTR1800017274. Registered 20 July 2018

Cardiac & Cardiovascular Systems

Endocrinology & Metabolism

Nontraditional lipid profiles

Peripheral artery disease

Hypertension

Epidemiology

Peripheral artery disease (PAD), considered as a clinical manifestation of systemic atherosclerosis, has been estimated to affect 200 million people globally and is a strong predictor of cardiovascular causes of death [1]. But PAD has not been fully understood and treated [2, 3]. Ankle-brachial index (ABI), the ratio of the systolic blood pressure (SBP) measured at the ankle to that measured at the brachial artery, has been proved as noninvasive diagnosis of PAD [4]. However, more than half of patients with PAD are asymptomatic, and the absence of routine ABI measurement in the primary care setting exists in most countries. There is an urgent need to find agents that can reliably indicate subclinical atherosclerosis for those at high risk of suffering from PAD.

Traditional lipid parameters, represented by abnormal rates of high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C), have been proved to be a common risk factor for PAD [5]. Interestingly, increasing studies have indicated development and progression of atherosclerosis on the condition of abnormal nontraditional lipid profile. It has recently been proposed that triglyceride (TG)/HDL-C ratio is a favorable predictor of cardiovascular disorders [6–9], and some studies have suggested that the total cholesterol (TC)/HDL-C ratio is also closely related to cardiovascular disease (CVD) [10–12]. Indeed growing evidence has established the associations between LDL-C/HDL-C ratio and carotid plaque score [13], carotid intima media thickness [14], and PAD [12]. Apart from these, non-high-density lipoprotein cholesterol (non-HDL-C), providing a measure of cholesterol contained in all atherogenic particles, has been proved as a better risk indicator for major adverse cardiovascular events than LDL-C by prospective observation study [15].

Furthermore, increasing researches show a strong link between hypertension and PAD [16]. In this scenario, identifying lipid-related risk factors in people with hypertension can help improve strategies for population-based screening and prevention of subjects at risk for vascular complications. However, few studies have investigated thoroughly the association between all nontraditional lipid indexes and PAD risk. At the same time, no previous study examined this association in the population with hypertension. In this case, we aimed to evaluate the relation between nontraditional lipid profile and the risk of PAD and sought to identify the best surrogate indicators for predicting an increased risk of PAD in Chinese adults with hypertension.

Subject population and design

The study population was from China Hypertension Registry Study (registration number: ChiCTR1800017274). The method of data collection and the exclusion criteria have been described previously [17]. Briefly, the study was a real world, multicenter, observational registry study designed to establish a national registry of patients with hypertension, investigate the prevalence and treatment of hypertension in China and assess the related factors affecting its prognosis. Eligible participants were men and women aged 18 years and older with hypertension, defined as seated resting SBP ≥ 140 mm Hg or/and diastolic blood pressure (DBP) ≥ 90 mm Hg at the screening, or who were on antihypertensive medications. The exclusion criteria included the following: (1) Psychological or nervous system impairment resulting in an inability to demonstrate informed consent; (2) Unable to be followed up according to the study protocol, or plans to relocate in the near future; (3) Those patients who are not suitable for inclusion or for long-term follow-up as assessed by study physicians. During March 2018 to August 2018, we recruited a total of 14,268 study participants in Wuyuan, Jiangxi Province, China as our study population. After excluding those without hypertension (n = 34), as well as with missing ABI (n = 3328) and lipid profiles value (n = 6), a total of 10,900 hypertensive participants were included in the analysis (Fig. 1).

The study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the Anhui Medical University Biomedical Institute. Informed written consent was obtained from all patients before their enrollment in this study.

Data Collection

Health interview was performed by trained research staff using questionnaire to collect demographic characteristics of the study population. Demographic information included age, sex, lifestyle data (such as alcohol drinking status, smoking status), medical history and medication information. The anthropometric measurements indicators included weight, height. Blood pressure (BP) measured by electronic sphygmomanometers.

After at least 12 hours overnight fasting, venous blood samples were obtained from all study participants. Next, the blood samples of all the subjects were collected, frozen and transported to the Biaojia Biotechnology laboratory for analysis in Shenzhen, China. Serum concentrations of fasting glucose, lipids (TC, TG, LDL-C and HDL-C), creatinine, total homocysteine (tHcy) were measured using automatic clinical analyzers (Beckman Coulter, USA) and the laboratory staffs were blind to the research protocol.

TC/HDL-C, TG/HDL-C, LDL-C/HDL-C were calculated as TC, TG, LDL-C divided by HDL-C, respectively. Non-HDL-C was calculated by subtracting HDL-C from TC. Body mass index (BMI) was calculated as the weight (in kilograms) divided by the squared height (in meters). Estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [18].

PAD

The presence of PAD was defined as an ABI < 0.9 in either leg [19]. The ABI was measured with the patients in the supine position according to standard clinical guidelines [20]. Measurements were performed after the participants had rested at least 10 minutes using the Omron Colin BP-203RPE III device (Omron Health Care, Kyoto, Japan). The ABI was calculated by dividing the highest SBP at the ankles by the highest SBP of the right or left upper arms. The lower of the ABI values calculated for the left and right ankles were used in the analysis.

Covariables

The covariates included in all the analyses were age, sex, BMI, SBP, DBP, smoking status, alcohol drinking status, fasting glucose, tHcy, eGFR, self-reported diabetes, self-reported stroke, lipoprotein-lowering drugs, and antihypertensive drugs.

Statistical Analyses

Continuous variables were presented as mean ± SD or median (interquartile range) and categorical variables were presented as percentage (%). The differences in population characteristics with or without PAD were compared using Student’s t-test or nonparametric Mann-Whitney test for continuous variables and chi-square test for categorical variables. Multivariate logistic regression analyses were used to assess the odds ratio (OR) and 95% confidence interval (CI) of the association between nontraditional lipid profiles (TC/HDL-C, TG/HDL-C, LDL-C/HDL-C ratios and non-HDL-C) and PAD with adjustment for pertinent variables. Nontraditional lipid profiles were evaluated using models for both continuous variables per SD increment and categorical variable using tertiles with the lowest tertile (T1) as the reference group. Trend tests were calculated by nontraditional lipid profiles tertiles categories as continuous variables. Moreover, the smooth curve fitting (penalized spline method) was used to visually show the relationship between nontraditional lipid profiles and PAD. The area under receiver-operating characteristic curves (AUCs) by receiver operating characteristic (ROC) analysis was calculated to compare the performance of different nontraditional lipid profiles as potential predictors of PAD, and the AUCs difference of these nontraditional lipid profiles were compared using DeLong’s test. Potential effect modification was evaluated by stratified analyses and interaction testing.

All data analysis was used the R software version 3.4.3 (www.R-project.org) and Empower version 2.20 (www.empowerstats.com, X&Y Solutions, Inc., Boston, MA). A 2-tailed P < 0.05 was considered to be statistically significant.

Characteristics of the subjects.

A total of 10,900 hypertensive patients were included in this final data analysis. Participant characteristics for all subjects and subjects with and without PAD were presented in Table 1. Overall, the mean (SD) age was 63.9 (9.3) years and 47.1% were males. Participants with PAD tended to have higher age, SBP, tHcy, TC/HDL-C ratio, LDL-C/HDL-C ratio, and have higher rate of males, current smoking, self-reported stroke, antihypertensive drugs and antiplatelet drugs, as well as have lower BMI, DBP, eGFR and HDL-C levles compared those without PAD (all P < 0.05). No significant differences were found between those with or without PAD in terms of fasting glucose, TC, TG, LDL-C, TG/HDL-C ratio, non-HDL-C levels, current alcohol drinking, self-reported diabetes, glucose-lowering drugs and lipoprotein-lowering drugs.

Table 1

Characteristics of study participants with or without PAD
Variables	Total (n = 10900)	non-PAD (n = 10590)	PAD (n = 310)	P value
Age, years	63.9 ± 9.3	63.6 ± 9.1	71.6 ± 10.0	< 0.001
Male, n (%)	5129 (47.1%)	4958 (46.8%)	171 (55.2%)	0.004
BMI, kg/m²	23.6 ± 3.8	23.6 ± 3.8	22.5 ± 3.9	< 0.001
SBP, mm Hg	148.5 ± 18.2	148.4 ± 18.0	152.8 ± 22.7	< 0.001
DBP, mm Hg	89.1 ± 11.5	89.2 ± 11.5	84.1 ± 11.5	< 0.001
Current smoking, n (%)	2868 (26.3%)	2745 (25.9%)	123 (39.7%)	< 0.001
Current alcohol drinking, n (%)	2469 (22.7%)	2409 (22.8%)	60 (19.4%)	0.159
Self-reported diabetes, n (%)	1176 (10.8%)	1145 (10.8%)	31 (10.0%)	0.65
Self-reported stroke, n (%)	708 (6.5%)	667 (6.3%)	41 (13.2%)	< 0.001
Laboratory results
Fasting glucose, mmol/L	6.2 ± 1.6	6.2 ± 1.6	6.1 ± 1.5	0.439
Total homocysteine, µmol/L	18.0 ± 11.0	17.9 ± 10.8	22.5 ± 17.1	< 0.001
eGFR, mL · min^− 1 · 1.73 m^− 2	88.7 ± 20.4	89.1 ± 20.1	74.8 ± 23.3	< 0.001
TC, mmol/L	5.1 ± 1.1	5.1 ± 1.1	5.1 ± 1.2	0.966
TG, mmol/L	1.4 (1.0-2.1)	1.4 (1.0-2.1)	1.4 (1.0-2.1)	0.069
LDL-C, mmol/L	3.0 ± 0.8	3.0 ± 0.8	3.1 ± 0.9	0.156
HDL-C, mmol/L	1.6 ± 0.4	1.6 ± 0.4	1.5 ± 0.4	0.001
TC/HDL-C ratio	3.4 ± 0.8	3.4 ± 0.8	3.5 ± 0.9	< 0.001
TG/HDL-C ratio	0.9 (0.6–1.5)	0.9 (0.6–1.5)	0.9 (0.6–1.5)	0.304
LDL-C/HDL-C ratio	2.0 ± 0.7	2.0 ± 0.6	2.1 ± 0.7	< 0.001
Non-HDL-C, mmol/L	3.6 ± 1.0	3.6 ± 1.0	3.6 ± 1.1	0.163
Medication use, n (%)
Antihypertensive drugs	7155 (65.6%)	6930 (65.4%)	225 (72.6%)	0.009
Glucose-lowering drugs	572 (5.2%)	554 (5.2%)	18 (5.8%)	0.654
Lipoprotein-lowering drugs	381 (3.5%)	369 (3.5%)	12 (3.9%)	0.715
Antiplatelet drugs	429 (3.9%)	409 (3.9%)	20 (6.5%)	0.021
Data are expressed as mean ± standard deviation or median (interquartile range) and numbers (percentage) as appropriate.
Abbreviations: PAD, peripheral arterial disease; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; TC, total cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; non-HDL-C, non-high-density lipoprotein cholesterol.

Stratified Analyses

Stratified analyses by subgroups defined by major covariables were performed to further confirm that the findings are robust given potential confounders. None of the stratified variables, including sex, age, BMI, current smoking, current alcohol drinking, SBP, tHcy and fasting glucose, significantly modified the association between four kinds of nontraditional lipid profiles and the risk of PAD (all P-interaction > 0.05) (see Additional file 1: Fig. S1-4).

In this sample of large rural residents, nontraditional lipid profiles are all positively associated with the risk of PAD in people with hypertension in China. The fully-adjusted smooth curve fitting showed that the relationships between nontraditional lipid profiles ratio and PAD were linear. Moreover, our results suggested that TC/HDL-C and LDL-C/HDL-C ratio were better indicators for early prediction of PAD risk.

To date, research findings on the association between nontraditional lipid profiles and arteriosclerotic cardiovascular disease (ASCVD) remain to be explored. In a prospective study including 107 patients with type 2 diabetes in Taiwan, Lee et al. found that TC/HDL-C showed an inverse trend to change in ABI (β = −0.212, 95% CI: −0.043-−0.001) [11]. Another post hoc data analysis from randomized controlled trial, conducted in 1599 community-based elderly cohort, reported that TC/HDL-C ratio (OR:1.31; 95% CI: 1.14–1.49), non-HDL-C (OR: 1.15; 95% CI: 1.01–1.31) and LDL-C/HDL-C ratio (OR:1.25; 95% CI:1.10–1.43) had a significant correlation with PAD [12]. Moreover, another population-based study from the elderly in rural China also found a significant correlation between LDL-C/HDL-C and PAD (highest compared with lowest tertile; OR: 2.56; 95% CI, 1.37 to 4.81) [21]. Additionally, Ridker et al. [22] and Pradhan et al. [23] separately reported the results concerning the association between TC/HDL-C ratio and PAD in male physicians and female health professionals in the United States. Both of them came to the same results that TC/HDL-C ratio was significantly associated with PAD. However, Tongdee et al. found that TC/HDL-C, TG/HDL-C and LDL-C/HDL-C failed to predict early subclinical atherosclerosis among perimenopausal/menopausal women [24]. A cross-sectional survey [25], based on 2982 elderly Beijing residents, found that TG/HDL-C ratio was not associated with low ABI (ABI ≤ 0.9) (highest compared with lowest quartile; OR: 1.64; 95% CI, 0.88 to 3.07; P ≥ 0.05). Besides, the study showed that the trends of the association between the TC/HDL-C and the risk of PAD were nonlinear. The PAD risk was almost identical on the left side of inflection point, and then increased linearly with when TC/HDL-C ≥ 3. Nevertheless, none of the previous studies had evaluated the role of each nontraditional lipid profiles in assessing the risk of PAD, especially in hypertensive population.

Those previous studies did not find the reason for the linear relationship explained by differences in patient characteristics, homocysteine (Hcy) levels, and adjustment of confounders. First, our study participants were those with hypertension, while the Lee et al’s study enrolled patients with Type 2 diabetes. It is possible that hypertension is heterogeneous for different diseases, the saturation point of injury is different in different diseases. Second, due to differences in regions and diet, lipid levels are significantly different, and baseline lipid levels may have an impact on the levels of lipid ratios and the prevalence of increased PAD. The high-carbohydrate diets of the Chinese populations might contribute to hypertriglyceridemia, while the standard Western high-fat diets are more likely to induce hypercholesterolemia [26]. Our study was conducted in a population with high-carbohydrate diets, while the Ridker et al’s study and Pradhan et al’s study were undertaken in regions with the standard high-fat diets. Indeed, obvious geographical difference in PAD incidence also exists in China [27]. Our study was carried out in the inland areas of the south, but Liang Y et al’s study and Zhan Y et al’s study were carried out in northern areas and Chi C et al’s study was carried out in the coastal areas. Third, the mean baseline tHcy was 18.0 µmol/L in our study, much higher than normal levels. tHcy would cause disorders of lipid metabolism and further atherosclerotic disease [28, 29]. As such, the association between nontraditional lipid profiles and PAD in a crowd of low tHcy concentrations is unable to be examined. Overall, current studies are just hypothesis-generating; further investigations are needed to confirm our results.

While the exact mechanisms by which nontraditional lipid index is able to point the risk of PAD remains to be delineated, it is biologically plausible. Firstly, significant alterations in nontraditional lipid profiles, probably as a consequence of dyslipidemia in the early stages of PAD, may be characterized as a state of miniaturized low-density lipoprotein particle (LDL-P), and decreased high-density lipoprotein particle (HDL-P). TC/HDL-C ratio, as an atherogenic particle burden, was associated to LDL-P and particle difference in low-density lipoprotein (LDL) might be attributed to a source of residual risk of cardiovascular events and a unique lipoprotein signature for PAD [30, 31]. In addition, previous studies showed that increased serum TG/HDL-C ratio was an independent predictor of a decreased LDL-P size [32]. Previous studies have shown that small dense LDL (sdLDL) promotes pro-atherogenic modifications with the characteristics of increased flux into the arterial intima and prolonged circulation time and reduced LDL receptor affinity [33, 34]. Moreover, TC/HDL-C and TG/HDL-C ratios may reflect the decreased mature large sized HDL-P, which is related to anti-atherosclerosis [26, 35, 36]. Non-HDL-C is a recognized risk factor for ASCVD because of its containment of all the atherogenic lipoproteins, and epidemiological survey showed that non-HDL-C is a stronger lipid parameter of atherogenesis compared to LDL-C [15]. Overall, TC/HDL-C ratio, TG/HDL-C ratio and non-HDL-C can indirectly prompt early PAD risk by reflecting the size and concentration of LDL-P, HDL-P and other atherosclerotic factors, such as chylomicron, very-low density lipoprotein (VLDL), intermediate density lipoprotein (IDL), which are all closely related to CVD. Secondly, TC/HDL-C ratio and TG/HDL-C ratio were seen as strong correlates of insulin resistance, which has been appreciated as a risk factor for the progression of PAD [37–39]. Thirdly, almost all participants (98.7%) in our study have hyperhomocysteinemia (HHcy, defined as tHcy ≥ 10 µmol/L) simultaneously, and HHcy may reflect the clinical significance of nontraditional lipid indexes by mediating changes in blood lipid levels and increased adverse effects of lipids on atherosclerosis. HHcy was proven to reduce high-density lipoprotein (HDL) content in circulation by promoting HDL-C clearance apart from diminishing apolipoprotein A-I composite [29, 40]. Furthermore, there are reasons to suggest that elevated LDL levels in patients with HHcy are more likely to produce atherosclerotic disease [41, 42]. Accordingly, there may be necessity on LDL-C/HDL-C ratio for the identification of early atherosclerosis risk as an alternative to the standard lipid profile in a population with HHcy. Have regard to the increasing number of studies that consider nontraditional lipid profiles better represent the underlying atherosclerotic process, it is reasonable to use nontraditional lipid profiles to assess the risk of atherosclerotic diseases.

Several potential limitations of our study should be noted. First, our study is a cross-sectional study, which makes it difficult to explain the causal relationship between non-traditional lipid profiles and PAD. Secondly, our study population is from rural hypertensive patients in southern China, and the study subjects are over 18 years old, so our results cannot be generalized to other age groups, regions, and types of diseases. Despite these shortcomings, our study is currently the largest study to assess the risk of PAD in non-traditional lipid mass spectrometry in hypertension patients.

Among Chinese hypertensive adults, all the nontraditional lipid profiles (TC/HDL-C, TG/HDL-C, LDL-C/HDL-C ratios, and non-HDL-C) were independently and positively associated with PAD. In addition, TC/HDL-C and LDL-C/HDL-C ratios could better predict the risk of PAD.

PAD

Peripheral Arterial Disease; TC:Total Cholesterol; TG:Triglyceride; HDL-C:High-Density Lipoprotein Cholesterol; LDL-C:Low-Density Lipoprotein Cholesterol; non-HDL-C:non-High-Density Lipoprotein Cholesterol; AUCs:Area Under Receiver-Operating Characteristic Curves; ABI:Ankle-Brachial Index; SBP:Systolic Blood Pressure; DBP:Diastolic Blood Pressure; CVD:Cardiovascular Disease; tHcy:Total Homocysteine; BMI:Body Mass Index; eGFR:Estimated Glomerular Filtration Rate; CKD-EPI:Chronic Kidney Disease Epidemiology Collaboration; OR:Odds Ratio; CI:Confidence Interval; ROC:Receiver Operating Characteristic; ASCVD:Arteriosclerotic Cardiovascular Disease; LDL-P:Low Density Lipoprotein Particle; HDL-P:High Density Lipoprotein Particle; sdLDL:Small Dense LDL; VLDL:Very Low Density Lipoprotein; IDL:Intermediate Density Lipoprotein; HHcy:Hyperhomocysteinemia;

Funding

This work was supported by the Science and Technology Innovation Platform Project of Jiangxi Province (Grant number: 20165BCD41005).

Availability of data and materials

The datasets generated and analyzed during the current study are not publicly available because this study is still on-going and the follow-up is not finished, but are available from the corresponding author on reasonable request.

Authors’ contributions

CCD and YC participated in the literature search, data analysis, and data interpretation. CCD wrote the manuscript. LHH extracted and collected data. XH, YMS, MHL, LHH, WZ, TW, LJZ conceived of the study and participated in its design and coordination. HHB and XSC participated in the study design and provided critical revision. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Consent for publication

All the authors have consented for the publication of this study.

Competing interests

The authors declare that they have no competing interests.

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Association Between Nontraditional Lipid Profiles and Peripheral Arterial Disease in Chinese adults with Hypertension

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