Fasting and non-fasting lipoproteins and apolipoproteins for long-term outcome prediction in Chinese patients with coronary heart disease：a prospective observational study

doi:10.21203/rs.3.rs-2218224/v1

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Research Article

Fasting and non-fasting lipoproteins and apolipoproteins for long-term outcome prediction in Chinese patients with coronary heart disease：a prospective observational study

https://doi.org/10.21203/rs.3.rs-2218224/v1

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Background

Within 24 hours a day, people are mostly in a non-fasting state. However, little is known about the characteristics and clinical significance of non-fasting lipids in Chinese population with coronary heart disease (CHD) in response to traditional Chinses diets.

Methods

A total number of 1022 Chinese CHD patients with coronary artery luminal stenosis more than 40% diagnosed by coronary artery angiography were enrolled. All the patients received the routine treatment for CHD, including statins. They were divided into intermediate stenosis group (luminal stenosis 40–70%, n = 486) or severe stenosis group (luminal stenosis > 70%, n = 536). Their blood lipid profiles were measured in the fasting state or 4 hours after normal breakfast. All the participants followed up for five years. Major adverse cardiovascular events (MACE) including all cause death, cardiac death, myocardial infarction, unscheduled coronary revascularization and stroke were recorded.

Results

After normal breakfast intake, patients with either intermediate or severe stenosis had an apparent increase from the fasting state in the levels of TG, remnant cholesterol (RC) and ApoA1, but a significant reduction in the levels of total cholesterol (TC), LDL-C, non-HDL-C, Apo B and Apo E. Multivariate logistic regression models showed that both the fasting and non-fasting levels of HDL-C and Apo A1 was negatively associated with the severity of coronary artery stenosis. In addition to the traditional risk factors (age, male, diabetes and smoking) and the severity of coronary artery stenosis, both the fasting and non-fasting levels of lipoproteins (LDL-C and HDL-C) and apolipoproteins (Apo A1 and Apo B) were identified as independent predictors of 5-year MACE occurrence by multivariate Cox proportional hazards analysis.

Conclusion

This prospective observational study demonstrated that the levels of lipoproteins and apolipoproteins in either fasting or non-fasting state were highly associated with the long-term risk of MACE in Chinses CHD patients. Measurements of lipid profiles in the non-fasting state may be feasible for CHD management in routine clinical practice in China.

Lipid

non-fasting state

coronary heart disease

major adverse cardiovascular events

coronary artery stenosis

Although people are mostly in a non-fasting state in a 24-hour period, lipid profiles to assess cardiovascular risk are conventionally measured in the fasting state [1, 2]. In fact, numerous observational studies have demonstrated that lipids and lipoproteins vary minimally in response to normal diet [3, 4, 5, 6, 7]. Non-fasting lipid measurement would not only simplify blood sampling for laboratories and clinicians but also improve patient compliance with lipid testing. Furthermore, various large scale prospective studies have demonstrated that the association of non-fasting lipid profiles with the risk of cardiovascular diseases are similar to fasting measurements [3, 4, 8, 9, 10]. A meta-analysis from the Emerging Risk Factors Collaboration have found that non-fasting non-HDL-C and non-fasting calculated LDL-C are even better than those evaluated in the fasting state for cardiovascular risk prediction [11]. Therefore, non-fasting lipid profiles has been accepted as the clinical standard in Denmark, based on recommendations from the Danish Society for Clinical Biochemistry since 2009 [12]. Thereafter, the UK NICE clinical guideline CG181 has endorsed the use of non-fasting lipid profiles in the cardiovascular primary prevention [13]. In 2016, the joint consensus statement from the European Atherosclerosis Society (EAS) and European Federation of Clinical Chemistry recommended the non-fasting blood samples for lipid testing in routine clinical practice [14].

Lipid profiles naturally change between individuals and between countries. Thus far, the information relating to non-fasting lipid profiles predominantly derived from western population-based studies. Very little is known about the characteristics and clinical significance of non-fasting lipids in Chinese population with coronary heart disease (CHD) in response to traditional Chinses diets. Therefore, we conducted a prospective observational study in Chinese CHD patients and examined their fasting and non-fasting lipid profiles. Furthermore, we analyzed the predictive value of non-fasting lipid profiles regarding to the risk of cardiovascular events during 5-year follow-up (Fig. 1).

Study population

This is a prospective observational study conducted at Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine. Our study complied with the declaration of Helsinki and was approved by the hospital ethnics review board (2016-256-T191). Informed consent was obtained from all the participants. A total number of 1203 patients with acute or stable chest discomfort and at least one cardiovascular risk factors were evaluated for enrollment in this study during the period between January 2015 and April 2017. All the patients underwent elective coronary artery angiography after admission. 1022 patients with intermediate or severe coronary lesions were finally enrolled and investigated. 181 patients were excluded because they had mild stenosis (< 40%) or negligible lesions in main coronary arteries and main branches. Patients with familial hyperlipidemia, severe valvular heart disease, severe cardiomyopathy, severe heart failure, thyroid disease, infectious disease, autoimmune diseases, serious lung diseases, sever liver and kidney disease, malignant tumor and other serious medical illness were also not included in the study.

All patients were routinely treated with anti-platelet drugs, β-blocker or angiotensin converting enzyme inhibitor (ACEI) or angiotensin II receptor blocker (ARB), nitrates, statins and /or other lipid-lowering drugs. Patients underwent percutaneous coronary intervention or coronary artery bypass graft surgery when their specialists deemed the procedure necessary and beneficial. All the demographic information, clinical data and laboratory findings were collected.

Coronary artery angiography

All participants underwent elective coronary angiography by the standard Judkin’s technique. The severity of coronary artery stenosis was assessed and quantified separately by 2 independent interventional physicians blind to the clinical data. A severe coronary lesion was defined as a luminal narrowing with a diameter stenosis of > 70% in any of the main coronary arteries, including the left main artery (LM), left anterior descending artery (LAD), left circumflex coronary artery (LCX) and right coronary artery (RCA), or main branches of the vascular systems (the diameter of the target vessel is ≥ 2.5 mm). An intermediate coronary lesion was defined as a luminal narrowing with a diameter stenosis of 40–70% in any of the main coronary arteries or ≥ 2.5 mm main branches of the vascular systems.

Blood collection and laboratory assay

Blood samples were collected after a 12-hour overnight fast and 4 hours after a daily breakfast according to their dietary habits. Plasma levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) were measured by biochemical auto-analyzer (Siemens Advia 2400). LDL-C was calculated from the Friedewald equation, LDL-C = TC − (HDL-C) − (TG/2.2) if TG was < 4.5 mmol/L. Otherwise, it was measured directly at higher triglyceride levels. Remnant cholesterol (RC) and non–HDL-C levels were calculated by the following equations, RC = TC − (HDL-C) − (LDL-C) and non–HDL-C = TC − (HDL-C).

Follow-up and major adverse cardiovascular events (MACE)

All the patients were followed every three months for 5 years in our outpatient clinic. However, if the patients could not attend their scheduled clinic appointment, they were interviewed by telephone. Follow-up was 100% complete. Major adverse cardiovascular events (MACE) were recorded during the period of follow-up. MACE was defined as the composite of all cause death, cardiac death, myocardial infarction, unscheduled coronary revascularization and stroke.

Statistical analysis

Statistical analysis was performed with SPSS version 21.0. Continuous variables were presented as median [first quartile, third quartile] and categorical variables were expressed as percentage. Differences of continuous variables between two groups were compared by Mann-Whitney U. Difference between fasting and non-fasting lipid profiles in a single group was compared by Wilcoxon signed-rank test. Difference of categorical variables was compared by Chi-square test. Multivariate logistic regression analysis (forward conditional) was performed to evaluate the independent factors associated with the severity of coronary artery stenosis. Clinical features and lipid profiles with p value < 0.05 in univariate analysis were included in multivariate logistic regression analysis. Odds ratios (OR) and 95% confidence intervals (CI) were calculated. Multivariate Cox proportional hazards regression analysis (forward conditional) was used to estimate the hazard ratio (HR) for the risk of MACE in a 5-year follow-up. Clinical features and lipid profiles with p value < 0.05 in univariate analysis were included in multivariate Cox regression analysis. Correlations between TC, HDL-C, LDL-C, non–HDL-C, Apo A1, and Apo B were assessed by Pearson correlation coefficient. A two-tailed p value of < 0.05 was considered statistically significant.

Demographic and clinical characteristics

Table 1 shows the baseline characteristics of the study participants. A total of 1022 CHD patients with angiographically > 40% coronary artery stenosis was included in the present study. 486 patients had intermediate coronary artery luminal stenosis (40%-70%) and 536 patients had severe luminal stenosis (> 70%). Compared with intermediate stenosis group, patients in severe stenosis group were older, more likely to be men, more smokers, more likely to have prior CHD history, had a higher prevalence of hypertension and diabetes mellitus. Patients with severe stenosis also tended to have higher proportions of acute coronary syndrome (ACS) and revascularization, higher levels of troponin I, B-type natriuretic peptide (BNP) and C-reaction protein (CRP) than those with intermediate stenosis. Moreover, the majority of participates received statins for at least three months before enrolling in the present study. Satins were administered to 356 and 446 patients in intermediate and severe stenosis group respectively (73.2% vs. 83.2%, p < 0.001).

Table 1

Baseline demographic and clinical characteristics of Chinese CHD patients with intermediate or severe coronary artery stenosis
	Intermediate stenosis (n = 486)	Severe stenosis (n = 536)	p value
Age (years)	66 [60, 73]	68[61, 75]	0.006
Male	252(51.9%)	374(69.8%)	< 0.001
BMI (kg/m²)	24.49[22.27, 26.57]	24.75[22.49, 26.81]	0.316
Type of CHD
ACS	33(6.8%)	134(25.0%)	< 0.001
Non-ACS	453(93.2%)	402(75.0%)	< 0.001
Revascularization
PCI	0(0%)	420(78.4%)	< 0.001
CABG	0(0%)	11(2.1%)	< 0.001
Other¹	486(100%)	105(19.6%)	< 0.001
Medical history
Smoker²	165(34.0%)	260(48.5%)	< 0.001
Hypertension	323(66.5%)	381(71.1%)	0.120
Diabetes mellitus	108(22.2%)	202(37.7%)	< 0.001
Prior history of CHD³	114(23.5%)	290(54.1%)	< 0.001
History of atrial fibrillation	61 (12.6%)	72(14.6%)	0.71
COPD	32(6.6%)	40(7.5%)	0.626
Family history of CVD	260(53.5%)	277(51.7%)	0.573
Medications
Aspirin and/or thienopyridine	465(95.7%)	509 (96.8%)	0.408
Anticoagulants	60(12.3%)	72(14.6%)	0.641
Beta blocker	115(23.6%)	133(24.9%)	0.715
ACEI/ARB	129(26.5%)	153(28.7%)	0.484
CCB	68(14.0%)	65(12.1%)	0.403
Statins	356(73.2%)	446(83.2%)	< 0.001
Other lipid-lowering drugs⁴	28(5.8%)	45(9.1%)	0.114
Laboratory variables
Troponin I (ng/ml)	0.00[0.00, 0.01]	0.01 [0.00, 0.05]	< 0.001
BNP (pg/ml)	49[24.75, 98.50]	66 [33.00, 182.00]	< 0.001
CRP (mg/L)	1.28[1.28, 4.29]	1.81[1.28, 6.50]	< 0.001
Creatine level (µmol/L)	78.00[67.00, 93.00]	81.00[67.00, 97.00]	0.118
Values are expressed as n (%) or median [first quartile, third quartil e]. ¹ Other refers to those who did not meet the standard for revascularization or refused to receive revascularization. ² Smokers include current smokers or former smokers who have quitted cigarette smoking for less than 10 years. ³ Prior history of CHD include prior myocardial infarction, prior coronary artery revascularization and documented coronary artery stenosis by angiography. ⁴ Other lipid-lowering drugs include cholesterol absorption inhibitor, fibrates, fish oil ect.

Fasting and non-fasting lipid profiles

Table 2 showed the fasting and non-fasting lipid profiles in the study population. Four hours after normal breakfast intake, patients with either intermediate or severe stenosis had an apparent increase from the fasting state in the levels of TG, RC and Apo A1, but a significant reduction in the levels of TC, LDL-C, non-HDL-C, Aop B and Apo E (Table 2). The non-fasting level of HDL-C significantly decreased from fasting state in severe stenosis group but not in intermediate stenosis group. No significant difference between fasting and non-fasting levels of lipoprotein(a) was observed in both groups. Moreover, both in the fast and non-fasting state, patients with severe stenosis tended to have lower levels of TC, LDL-C, HDL-C, non-HDL-C, Apo E and Apo A1 than patients with intermediate stenosis. It may be due to the higher proportion of patients receiving statins in sever stenosis group.

Table 2

Fasting and non-fasting lipid profiles in Chinese CHD patients with intermediate or severe coronary artery stenosis
	Intermediate stenosis (n = 486)			Severe stenosis (n = 536)			p value³	p value⁴
	Fasting	Non-fasting	p value¹	Fasting	Non-fasting	p value²	p value³	p value⁴
TC (mmol/L)	4.18[3.61, 4.86]	4.08[3.52, 4.69]	0.001	3.93[3.23, 4.64]	3.68[3.12, 4.33]	< 0.001	< 0.001	< 0.001
TG (mmol/L)	1.45[1.07, 2.02]	1.63[1.19, 2.25]	< 0.001	1.52[1.12, 2.14]	1.65[1.20, 2.31]	< 0.001	0.099	0.570
LDL-C (mmol/L)	2.36[1.87, 2.94]	2.21[1.72, 2.72]	< 0.001	2.16[1.62, 2.81]	1.89[1.45, 2.46]	< 0.001	0.001	< 0.001
HDL-C (mmol/L)	1.02[0.87, 1.23]	1.01[0.87, 1.22]	0.703	0.92[0.77, 1.11]	0.90[0.77, 1.08]	< 0.001	< 0.001	< 0.001
Lipoprotein (a) (g/L)	0.07[0.04, 0.15]	0.08[0.05, 0.17]	< 0.001	0.09[0.05, 0.20]	0.09[0.05, 0.21]	< 0.001	0.096	0.117
RC (mmol/L)	0.66[0.49, 0.91]	0.74[0.54, 1.02]	< 0.001	0.69[0.50, 0.97]	0.75[0.55, 1.05]	< 0.001	0.120	0.603
Non-HDL-C (mmol/L)	3.14[2.55, 3.73]	3.00[2.48, 3.61]	< 0.001	2.97[2.31, 3.66]	2.72[2.21, 3.32]	< 0.001	0.024	< 0.001
ApoA1(g/L)	1.11[0.99, 1.25]	1.17[1.04, 1.30]	< 0.001	1.05[0.93, 1.18]	1.08[0.97, 1.22]	< 0.001	< 0.001	< 0.001
ApoB (g/L)	0.83[0.69, 1.00]	0.80[0.68, 0.96]	< 0.001	0.82[0.65, 1.00]	0.75[0.63, 0.91]	< 0.001	0.257	0.001
ApoE (mg/dl)	4.13[3.38, 5.03]	4.02[3.40, 4.96]	0.008	3.85[3.11, 4.86]	3.69[2.97, 4.64]	< 0.001	0.001	< 0.001
Values are expressed as median [first quartile, third quartile]. ¹ Comparison of lipid profiles between fasting state and non-fasting state in intermediate stenosis group. ² Comparison of lipid profiles between fasting state and non-fasting state in severe stenosis group. ³ Comparison of fasting lipid profiles between intermediate and severe stenosis groups. ⁴ Comparison of non-fasting lipid profiles between intermediate and severe stenosis groups.

Fasting or non-fasting lipid profiles and the severity of coronary artery stenosis

Univariate logistic regression analysis was performed to identify the potential factors associated with the severity of coronary artery stenosis. As shown in Table 3 and Table 4, clinical features (age, male, smoker, diabetes mellitus and prior history of CHD), fasting and non-fasting levels of lipoproteins (TC, LDL-C, HDL-C) and apolipoproteins (ApoA1, Apo B and Apo E) were significantly related to the severity of coronary artery stenosis. The levels of Apo B and non-HDL-C were highly correlated with LDL-C, while HDL-C was strongly associated with Apo A1 (Figure S1). Therefore, the levels of lipoproteins and apolipoproteins were separately entered into the multivariate logistic regression models and the non-HDL-C level was not included in multivariate regression analysis. In the fasting-state multivariate logistic regression model (model 1 and 3), HDL-C (OR 0.262, 95% CI 0.158–0.436, p < 0.001) and Apo A1 (OR 0.198, 95% CI 0.099–0.396, p < 0.001) were negatively associated with the stenosis severity. Similar pattern was seen in the non-fasting-state multivariate regression model (model 2 and model 4). HDL-C (OR0.177, 95% CI 0.104–0.303, p < 0.001), Apo A1 (OR 0.158, 95% CI 0.077–0.324, p < 0.001) and Apo E (OR0.880, 95% CI 0.801–0.967, p < 0.001) in the non-fasting state were significantly associated with the severity of luminal stenosis. In addition, male, diabetes mellitus and prior history of CHD were also correlated with the increased risk of severe luminal stenosis in multivariate regression models.

Table 3

The association of coronary artery stenosis severity with lipoproteins
	Univariate logistic regression			Multivariate logistic regression
	OR	95%CI	p value	OR	95%CI	p value
Model 1 (fasting state)
Age	1.017	1.005–1.030	0.007	1.019	1.005–1.033	0.008
Male	2.144	1.659–2.770	< 0.001	2.180	1.648–2.883	< 0.001
Smoker¹	1.833	1.423–2.360	< 0.001
Diabetes mellitus	2.117	1.606–2.790	< 0.001	2.002	1.482–2.705	< 0.001
Prior history of CHD²	3.878	2.960–5.082	< 0.001	3.758	2.829–4.993	< 0.001
TC (mmol/L)	0.833	0.743–0.935	0.002
LDL-C (mmol/L)	0.840	0.732–0.964	0.013
HDL-C (mmol/L)	0.254	0.158–0.406	< 0.001	0.262	0.158–0.436	< 0.001
Model 2 (non-fasting state)
Age	1.017	1.005–1.030	0.007	1.020	1.006–1.034	0.005
Male	2.144	1.659–2.770	< 0.001	2.156	1.627–2.857	< 0.001
Smoker¹	1.833	1.423–2.360	< 0.001
Diabetes mellitus	2.117	1.606–2.790	< 0.001	2.014	1.487–2.727	< 0.001
Prior history of CHD²	3.878	2.960–5.082	< 0.001	3.809	2.860–5.073	< 0.001
TC (mmol/L)	0.701	0.615–0.799	< 0.001
LDL-C (mmol/L)	0.717	0.614–0.837	< 0.001
HDL-C (mmol/L)	0.186	0.113–0.304	< 0.001	0.177	0.104–0.303	< 0.001
Values are expressed as median [first quartile, third quartile]. ¹ Smokers include current smokers or former smokers who have quitted cigarette smoking for less than 10 years. ² Prior history of CHD include prior myocardial infarction, prior coronary artery revascularization and documented coronary artery stenosis by angiography.

Table 4

The association of coronary artery stenosis severity with apolipoproteins
	Univariate logistic regression			Multivariate logistic regression
	OR	95%CI	p value	OR	95%CI	p value
Model 3 (fasting state)
Age	1.017	1.005–1.030	0.007	1.018	1.004–1.032	0.011
Male	2.144	1.659–2.770	< 0.001	2.196	1.662–2.902	< 0.001
Smoker¹	1.833	1.423–2.360	< 0.001
Diabetes mellitus	2.117	1.606–2.790	< 0.001	1.997	1.480–2.695	< 0.001
Prior history of CHD²	3.878	2.960–5.082	< 0.001	3.824	2.880–5.076	< 0.001
ApoA1(g/L)	0.209	0.111–0.395	< 0.001	0.198	0.099–0.396	< 0.001
ApoB (g/L)	0.806	0.488–1.329	0.397
ApoE (mg/dl)	0.883	0.815–0.955	0.002
Model 4 (non-fasting state)
Age	1.017	1.005–1.030	0.007	1.018	1.004–1.033	0.010
Male	2.144	1.659–2.770	< 0.001	2.117	1.597–2.805	< 0.001
Smoker¹	1.833	1.423–2.360	< 0.001
Diabetes mellitus	2.117	1.606–2.790	< 0.001	2.007	1.483–2.717	< 0.001
Prior history of CHD²	3.878	2.960–5.082	< 0.001	3.816	2.865–5.083	< 0.001
ApoA1(g/L)	0.143	0.075–0.272	< 0.001	0.158	0.077–0.324	< 0.001
ApoB (g/L)	0.472	0.282–0.821	< 0.001
ApoE (mg/dl)	0.819	0.750–0.895	< 0.001	0.880	0.801–0.967	< 0.001
Values are expressed as median [first quartile, third quartile]. ¹ Smokers include current smokers or former smokers who have quitted cigarette smoking for less than 10 years. ² Prior history of CHD include prior myocardial infarction, prior coronary artery revascularization and documented coronary artery stenosis by angiography.

Fasting or non-fasting lipid profiles and clinical outcomes during a 5-year follow-up

During 5-year follow up, 43 patients (8.85%) in intermediate stenosis group and 113 patients (21.08%) in severe stenosis group eventually developed MACE. In multivariate Cox regression models (model 1 and model 3) adjusting for nonlipid classical risk factors (age, male, smoking, diabetes and stenosis severity), fasting levels of lipoproteins (LDL-C and HDL-C) and apolipoproteins (Apo A1 and Apo B) were strongly associated with the risk of MACE (Tables 5 and 6). Non-fasting levels of LDL-C, HDL-C, Apo A1 and Apo B had similar association with MACE in multivariate Cox regression models (Model 2 and 4) (Tables 5 and 6). LDL-C and Apo B in either fasting state (LDL-C: HR 1.592, 95%CI 1.349–1.878; Apo B: HR 6.538, 95%CI 3.614–11.827; both p < 0.001) or non-fasting state (LDL-C: HR 1.657, 95%CI 1.381–1.987; Apo B: HR 5.350, 95%CI 2.793–10.249; both p < 0.001) were associated with the increased risk of MACE. In contrast, HDL-C and Apo A1 in fasting (HDL-C: HR 0.248, 95%CI 0.122–0.504; Apo A1: HR0.199, 95%CI 0.083–0.477; both p < 0.001) or non-fasting state (HDL-C: HR 0.130, 95%CI 0.060–0.280; Apo A1: HR 0.128, 95%CI0.054-0.305; both p < 0.001) were negatively correlated with the occurrence of MACE.

Table 5

The risk for 5-year MACE occurrence and lipoproteins
	Univariate Cox regression			Multivariate Cox regression
	HR	95%CI	p value	HR	95%CI	p value
Model 1 (fasting state)
Coronary artery stenosis severity	2.284	1.604–3.253	< 0 .001	1.764	1.220–2.551	0.003
Age	1.021	1.004–1.038	0.013	1.022	1.006–1.039	0.008
Male	1.589	1.125–2.243	0.008
Smoker¹	1.611	1.172–2.215	0.003	1.464	1.061–2.020	0.020
Diabetes mellitus	2.028	1.480–2.779	< 0 .001	1.789	1.297–2.467	< 0 .001
TC (mmol/L)	1.209	1.057–1.383	0.006
LDL-C (mmol/L)	1.364	1.166–1.596	< 0.001	1.592	1.349–1.878	< 0.001
HDL-C (mmol/L)	0.341	0.180–0.648	0.001	0.248	0.122–0.504	< 0.001
Model 2 (non-fasting state)
Coronary artery stenosis severity	2.284	1.604–3.253	< 0 .001	1.740	1.203–2.517	0.003
Age	1.021	1.004–1.038	0.013	1.021	1.004–1.038	0.013
Male	1.589	1.125–2.243	0.008
Smoker¹	1.611	1.172–2.215	0.003	1.444	1.045–1.994	0.026
Diabetes mellitus	2.028	1.480–2.779	< 0 .001	1.830	1.328–2.524	< 0.001
TC (mmol/L)	1.102	0.946–1.284	0.211
LDL-C (mmol/L)	1.298	1.093–1.542	0.003	1.657	1.381–1.987	< 0.001
HDL-C (mmol/L)	0.191	0.095–0.387	< 0.001	0.130	0.060–0.280	< 0.001
Values are expressed as median [first quartile, third quartile]. ¹Smokers include current smokers or former smokers who have quitted cigarette smoking for less than 10 years.

Table 6

The risk for 5-year MACE occurrence and apolipoproteins
	Univariate Cox regression			Multivariate Cox regression
	HR	95%CI	p value	HR	95%CI	p value
Model 3 (fasting state)
Coronary artery stenosis severity	2.284	1.604–3.253	< 0 .001	1.772	1.226–2.562	0.002
Age	1.02	1.004–1.038	0.013	1.025	1.008–1.042	0.003
Male	1.589	1.125–2.243	0.008	1.448	1.021–2.054	0.038
Smoker¹	1.611	1.172–2.215	0.003
Diabetes mellitus	2.028	1.480–2.779	< 0 .001	1.846	1.339–2.546	< 0.001
ApoA1(g/L)	0.234	0.101–0.541	0.001	0.199	0.083–0.477	< 0.001
ApoB (g/L)	4.246	2.413–7.470	< 0.001	6.538	3.614–11.827	< 0.001
ApoE (mg/dl)	1.013	0.925–1.111	0.775
Model 4 (non-fasting state)
Coronary artery stenosis severity	2.284	1.604–3.253	< 0 .001	1.758	1.213–2.549	0.003
Age	1.021	1.004–1.038	0.013	1.022	1.006–1.039	0.009
Male	1.589	1.125–2.243	0.008
Smoker¹	1.611	1.172–2.215	0.003	1.384	1.003–1.911	0.048
Diabetes mellitus	2.028	1.480–2.779	< 0 .001	1.834	1.330–2.529	< 0.001
ApoA1(g/L)	0.107	0.044–0.258	< 0.001	0.128	0.054–0.305	< 0.001
ApoB (g/L)	3.689	1.961–6.943	< 0.001	5.350	2.793–10.249	< 0.001
ApoE (mg/dl)	0.967	0.877–1.066	0.498
Values are expressed as median [first quartile, third quartile]. Apo, apolipoprotein. MACE, major adverse cardiovascular events. ¹Smokers include current smokers or former smokers who have quitted cigarette smoking for less than 10 years.

This prospective observational study investigated the clinical significance of fasting and non-fasting lipid profiles in Chinese CHD patients. All the participants had luminal stenosis > 40% in the main branches of coronary arteries and most of them had received statins for at least three months before enrollment. We found that CHD patients with either intermediate (40%-70%) or severe stenosis (> 70%) had an apparent change from the fasting state to four hours after normal food intake in the levels of lipoproteins and apolipoproteins. Although the level of lipids altered in response to daily diet, both fasting and non-fasting levels of lipoproteins and apolipoproteins had similar predictive value for MACE in Chinese CHD patients, regardless of the severity of coronary artery stenosis, age, male, smoking or diabetes. LDL-C and Apo B in either fasting or non-fasting state had strong association with increased MACE risk in CHD (fasting: HR 1.592 and 6.538, non-fasting: HR 1.657 and 5.350; both p < 0.001). On the contrary, fasting and non-fasting levels of HDL-C and Apo A1 were negatively association with MACE risk (fasting: HR 0.248 and 0.199, non-fasting: HR 0.130 and 0.128; both p < 0.001). Even though fasting lipid measurement is currently recommended by the guidelines in China, our findings have suggested the feasibility of using non-fasting lipids for CHD management in routine clinical practice.

For many years, most societies, guidelines, and statements has recommended to measure lipid profiles in the fasting state for cardiovascular risk assessment. This may be due to the dynamic changes observed in some lipid components, especially triglyceride during a postprandial (high-fat tolerance) test. In fact, people eat much less fat in a normal daily life and they are also mostly in a non-fasting state within 24 hours a day. Thereafter, several large-scale, population-based studies including children, women, men, and diabetic patients compared the fasting and non-fasting levels of lipids in response to daily food intake [3–7]. They found a slight elevation in non-fasting TG (0.1-0.3mmol/L or 10–21% increase from fasting state) [3–7] and minor decline in non-fasting TC (0.1-0.3mmol/L or 1–8% reduction from fasting state) and LDL-C (0.1–0.3 mmol/L or 4–9% reduction from fasting state) [3, 4, 6, 7]. However, the alteration between fasting and non-fasting HDL-C levels remained inconsistent. Based on the Copenhagen General Population Study, the maximal mean change at 1–6 h after habitual meals was − 0.1mmol/L for HDL-C [3]. Some studies showed that non-fasting HDL-C level remained unchanged in children aged 12 years or older, or in the large community-based cohort [6, 7]. Taken together, these studies suggested that lipids and lipoproteins changed slightly in response to normal food intake in both men, women, and children.

The effect of daily food intake on plasma lipids has been fully evaluated in western-population based studies. However, the characteristics of non-fasting lipids in Chinese CHD population after traditional Chinese food intake has rarely been investigated. Previous studies showed that compared with fasting levels, overall levels of TC and LDL-C gradually decreased from 1 to 4 hours following normal food intake and TG level increased up to 6 hours after the last meal [3, 15]. Hence, the non-fasting blood samples for lipid measurement were collected 4 hours after a daily breakfast in the present. We found that CHD patients with either intermediate or severe stenosis had a significant reduction from fasting state in the levels of non-fasting TC, LDL-C, and non-HDL-C. An obvious increase in non-fasting levels of TG and RC was present only in CHD patients with intermediate stenosis whereas a significant reduction in non-fasting HDL-C was obtained in severe stenosis group but not in intermediate stenosis group. Overall, the pattern of difference between fasting and non-fasting lipoproteins in the present study are in line with previous large-scale cohort studies in Western populations [3–7]. The alterations of lipoproteins after food intake is possibly attributed to overproduction and decreased catabolism of triglyceride-rich lipoproteins and their remnants, especially in patients with hypertriglyceridemia, metabolism syndrome or diabetes [16, 17]. Transfer of triglycerides from triglyceride-rich lipoproteins to HDL and LDL particles in exchange for cholesteryl esters leads to reduced levels of HDL-C and LDL-C in non-fasting state [18].

Notably, the present study found significant changes in the levels of apolipoproteins from fasting to non-fasting state were observed in CHD patients with either intermediate or severe stenosis. However, the Danish general population study, the Copenhagen General Population Study and the Copenhagen City Heart Study have showed that Apo B, and Apo A1 do not change in response to normal food intake [3]. The discrepancy may be due to different study population and different dietary habit.

In order to explore the clinical significance of non-fasting lipid profiles in response to daily diet in Chinese CHD patients, the association of fasting or non-fasting lipid profiles with the stenosis severity of coronary artery was evaluated. In the univariable logistic regression model, both fasting and non-fasting TC, LDL-C, HDL-C and Apo A1 were significantly correlated the severity of coronary artery stenosis. By multivariate logistic regression analysis, fasting or non-fasting HDL-C and Apo A1 remained to be associated with the stenosis severity, in addition to the classical risk factors, including age, male, diabetes mellitus and prior CHD history.

Furthermore, the present study evaluated the significance of non-fasting lipoproteins and apolipoproteins in long-term MACE risk assessment in CHD patients. Both the fasting and non-fasting levels of lipoproteins (LDL-C and HDL-C) and apolipoproteins (Apo A1 and Apo B) were identified as independent predictors of 5-year MACE risk by multivariate Cox proportional hazards analysis, besides the conventional risk factors (age, male, diabetes and smoking) and the severity of coronary artery stenosis. Our findings are consistent with numerous large-scale, prospective studies with long-term follow-up. These previous studies have demonstrated that non-fasting lipid levels are equally solid as risk predictors for cardiovascular disease and mortality compared with fasting lipid profiles [3, 4, 8–10]. A meta-analysis from the Emerging Risk Factors Collaboration enrolled 68 long-term prospective studies, more than 300000 individuals, mostly in Europe and North America and analyzed the association of major lipids and apolipoproteins with the risk of vascular disease [11]. They found that the strength of the association between lipoproteins and CHD risk was not attenuated in the 20 studies using non-fasting lipid measurements. HR for vascular disease risk with lipid levels were at least as strong in non-fasting state as in fasting state [11].

In 2009, the Danish Society of Clinical Biochemistry firstly made an official recommendation on measuring lipids in the non-fasting state for cardiovascular risk prediction [12]. Subsequently, the American Heart Association (AHA) [19], National Institute for Health and Care Excellence (NICE) [13], the European Atherosclerosis Society and the European Federation of Clinical Chemistry [20], the Canadian Cardiovascular Society [21, 22] as well as other societies [23] have updated their guidelines or statement and recommended non-fasting lipid profiles for cardiovascular risk prediction. Additionally, some major statin trials, such as Heart Protection Study [24], Anglo-Scandinavian Cardiac Outcomes Trial [25], Study of the Effectiveness of Additional Reductions in Cholesterol and Homocysteine [26], used non-fasting blood sampling for lipid assessment. Although prospective studies have suggested the advantages and clinical significance of non-fasting lipids for cardiovascular risk prediction, there are lack of cost-effectiveness studies [27–29]. Driver et al. pointed that clinicians should take careful considerations of clinical scenarios (initial cardiovascular risk assessment, residual risk of CHD, diagnosis of familial hyperlipidemia or metabolic syndrome etc.) when choosing between fasting and non-fasting lipids [30].

In current China, the levels of lipids in fasting state are still routinely used in the cardiovascular risk assessment. Our study has provided preliminary evidence on the value of non-fasting lipoproteins and apolipoproteins in cardiovascular risk assessment in Chinese CHD patients. Meanwhile, Lin et al. suggested that the non-fasting LDL-C level could replace the fasting value to guide treatment in Chinese CHD patients when the fasting LDL-C level was < 1.4 mmol/L [15]. Taken together, more research in large-scale Chinese population is indispensable to evaluate the association between non-fasting lipid profiles and cardiovascular risk. If non-fasting lipid profiles are accepted to assess cardiovascular risk throughout the world, it would greatly simplify clinical care for both medical practitioner and patients.

This study has some limitations that should be acknowledged. Firstly, we investigated CHD patients with intermediate or severe stenosis, most of whom received statins therapy. Our findings cannot be applied to the newly diagnosed CHD population who have not received standard treatment. Secondly, the lipid profiles were not regularly monitored and the proportion of patients reaching the target LDL-C levels (< 1.4 mmol/L) was not carefully evaluated during the follow up. Thirdly, non-fasting lipid profiles are affected by food habit, but we did not examine the patients’ dietary intake, alcohol use or use of supplements in the study.

The present study demonstrated that besides classical risk factors and the severity of coronary artery stenosis, the levels of lipoproteins and apolipoproteins in either fasting or non-fasting state were independent predictors associated with the long-term risk of MACE in Chinses CHD patients. Measurements of lipid profiles in the non-fasting setting may be rational and feasible for the management of cardiovascular risk in Chinese CHD patients.

ACEI

angiotensin converting enzyme inhibitor

ACS

acute coronary syndrome

ARB

angiotensin II receptor blocker

ASCVD

atherosclerotic cardiovascular disease

BMI

body mass index

BNP

B-type natriuretic peptide

CABG

coronary artery bypass graft

CHD

coronary heart disease

confidence intervals

COPD

chronic obstructive pulmonary disease

CRP

C-reaction protein

CVD

cardiovascular disease

HDL-C

high-density lipoprotein cholesterol

hazard ratio

LAD

left anterior descending artery

LCX

left circumflex coronary artery

LDL-C

low-density lipoprotein cholesterol

left main artery

MACE

major adverse cardiovascular events

odds ratios

PCI

percutaneous coronary intervention

remnant cholesterol

RCA

right coronary artery

SAP

stable angina pectoris

total cholesterol

triglyceride

Ethics approval and consent to participate

The study was approved by Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine Ethnics Review Board (2016-256-T191). Informed consent was obtained from all the participants.

Consent for publication

Not applicable

Data availability statement

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This work was supported by Natural Science Foundation of Shanghai (Grant No. 21ZR1438000) and National Natural Science Foundation of China (Grant No. 81570037)

Authors' contributions

JZ and ZT collected the clinical data and followed up the participants. JJ and HS measured the lipid profiles and analyzed the data. HZ and CW performed coronary angiography. JG substantively revised the manuscript. CW and HZ designed the study and interpreted the data. HZ drafted the manuscript. All authors read and approved the final manuscript.

Acknowledgements

Not applicable

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No competing interests reported.

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Fasting and non-fasting lipoproteins and apolipoproteins for long-term outcome prediction in Chinese patients with coronary heart disease：a prospective observational study

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Background

Methods

Study population

Coronary artery angiography

Blood collection and laboratory assay

Follow-up and major adverse cardiovascular events (MACE)

Statistical analysis

Results

Demographic and clinical characteristics

Fasting and non-fasting lipid profiles

Fasting or non-fasting lipid profiles and the severity of coronary artery stenosis

Fasting or non-fasting lipid profiles and clinical outcomes during a 5-year follow-up

Discussion

Conclusion

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