Demographic and clinical characteristics of participants at baseline
There were no significant differences in age, gender, BMI, smoking history, hypercholesterolemia, diabetes mellitus, atrial fibrillation, stroke, hypertension, and medications between the ACS and non-ACS groups (Table 1).
Table 1
Clinical characteristics of the study population.
|
non-ACS
|
ACS
|
|
(n = 111)
|
(n = 256)
|
Medical history
|
|
|
Age, years
|
60.63±10.74
|
61.88±11.21
|
Male sex, n (%)
|
68(61.26)
|
178(69.53)
|
Heart rate, bpm
|
70.98±8.92
|
72.72±11.87
|
Systolic pressure, mmHg
|
131.87±15.93
|
134.07±19.29
|
BMI, kg/m2
|
24.83±3.80
|
24.88±3.54
|
Smoker, n (%)
|
19(17.12)
|
50(19.53)
|
Hypertension, n (%)
|
62(55.86)
|
138(53.91)
|
Hyperlipidemia, n (%)
|
35(31.53)
|
65(25.39)
|
Diabetes mellitus, n (%)
|
15(13.51)
|
46(17.97)
|
Atrial fibrillation, n (%)
|
2(1.80)
|
5(1.95)
|
Stroke, n (%)
|
6(5.41)
|
15(5.86)
|
Medication
|
|
|
Antiplatelet, n (%)
|
101(90.99)
|
244(95.31)
|
Anticoagulant, n (%)
|
61(54.95)
|
196(76.56)
|
Lipid-lowering agent, n (%)
|
98(88.29)
|
232(90.63)
|
ACE inhibitor/ARB, n (%)
|
35(31.53)
|
107(41.80)
|
β-blockers, n (%)
|
49(44.14)
|
155(60.55)
|
Nitrate esters, n (%)
|
35(31.53)
|
125(48.83)
|
Proton pump inhibitors, n (%)
|
87(78.38)
|
172(67.19)
|
Biochemical and hematological data
|
|
|
Glucose, mmol/L
|
5.42±1.97*
|
6.17±2.94
|
Creatinine, µmol/L
|
69.52±12.93*
|
74.41±21.19
|
Uric acid, µmol/L
|
338.15±83.775
|
334.01±98.38
|
Cholesterol, mmol/L
|
4.49±3.83
|
4.08±1.28
|
High Density Lipoprotein, mmol/L
|
1.08±0.29*
|
0.98±0.27
|
Low Density Lipoprotein, mmol/L
|
2.45±0.85
|
2.37±0.89
|
Apolipoprotein A, mmol/L
|
1.20±0.29*
|
1.11±0.27
|
Apolipoprotein B, mmol/L
|
0.84±0.28
|
0.81±0.29
|
LP (a), mmol/L
|
334.66±267.41*
|
385.89±337.51
|
Triglycerides, mmol/L
|
1.73±1.56
|
2.02±2.33
|
MB isoform of creatine kinase, IU/L
|
12.81±8.20*
|
38.47±60.53
|
Troponin I, ng/mL
|
0.40±0.30*
|
3.43±8.83
|
Platelets, *10^9/L
|
206.57±60.49
|
210.45±69.00
|
Leukocytes, *10^9/L
|
6.42±1.76
|
7.56±2.50
|
Neutrophils, *10^9/L
|
3.88±1.40*
|
5.09±2.45
|
Lymphocytes (%)
|
30.56±8.54*
|
25.49±9.56
|
Neutrophils (%)
|
59.13±9.38*
|
65.17±11.02
|
Monocytes (%)
|
6.82±1.98
|
6.71±2.10
|
Eosinophils (%)
|
2.37±1.66
|
2.02±2.12
|
Basophils (%)
|
0.32±0.56
|
0.26±0.55
|
Data are presented as mean±SD.
|
*p<0.05 was statistically significant when comparisons were made among the non-ACS and ACS group.
|
Table 2
The level of inflammation biomarkers and scores
|
non-ACS
|
ACS
|
|
(n = 111)
|
(n = 256)
|
Plasma BPI (ng/mL)
|
16.23±13.19*
|
46.42±16.61
|
Hs-CRP (pg/mL)
|
17699.58±16501.09*
|
40355.17±8389.56
|
IL-1β (pg/mL)
|
2509.66±1680.89*
|
4843.68±1076.73
|
MPO-DNA (ng/mL)
|
456.39±304.33*
|
890.63±382.67
|
S100A8/A9 (ng/mL)
|
11.74±7.61*
|
19.54±8.71
|
TIMI score
|
1.73±1.13*
|
3.24±1.45
|
GRACE score
|
107.41±23.84*
|
129.10±33.47
|
Gensini score
|
21.01±32.16*
|
56.98±35.62
|
BPI, bactericidal/permeability increasing protein
|
IL-1β, interleukin-1 β
|
Hs-CRP, high sensitivity C-reactive protein
|
Data are presented as mean±SD
|
*p<0.05 was statistically significant when comparisons were made among the non-ACS and ACS group
|
There were no significant differences in the levels of uric acid, cholesterol, LDL, apolipoprotein B, triglycerides, numbers of platelets and leukocytes, and percentages of monocytes, eosinophils, and basophils between the ACS and non-ACS groups. The level of creatinine in the non-ACS group was significantly lower than that of the ASC group (69.52 ± 12.93 vs. 74.41 ± 21.19 µmol/L, p < 0.05). Patients with ASC had significantly higher levels of glucose (6.17 ± 2.94 vs. 5.42 ± 1.97 mmol/L) and Lp (a) (385.89 ± 337.51 vs. 334.66 ± 267.41 mmol/L), an increased number of neutrophils (5.09 ± 2.45 vs. 3.88 ± 1.40 * 10^9/L), and a higher percentage of neutrophils (65.17 ± 11.02 vs. 59.13 ± 9.38), but lower levels of HDL (2.37 ± 0.89 vs. 2.45 ± 0.85 mmol/L) and apolipoprotein A (1.11 ± 0.27 vs. 1.20 ± 0.29 mmol/L), and a lower percentage of lymphocytes (25.49 ± 9.56 vs. 30.56 ± 8.54) compared with the non-ACS group (all p < 0.05) (Table 1).
Plasma BPI levels were significantly higher in the ACS group compared to the non-ACS group
The ACS group showed significantly higher plasma levels of BPI compared with the non-ACS group (46.42 ± 16.61 vs. 16.23 ± 13.19 ng/mL, p < 0.05) (Table 2, Figure 1a).
Levels of Hs-CRP, IL-1β, MPO-DNA, and S100A8/A9 in the ACS and control groups
Plasma levels of hs-CRP, IL-1β, MPO-DNA, and S100A8/A9 in the ACS group were significantly higher compared with the non-ACS group (all p < 0.05) (Table 2).
TIMI, GRACE, and Gensini scores in the ACS and control groups
The TIMI, GRACE, and Gensini scores of the ACS group were significantly higher compared with the non-ACS group (all p < 0.05) (Table 2).
Correlation of plasma BPI levels with traditional risk factors and circulating inflammatory biomarkers
To investigate the clinical relevance of high plasma BPI levels in ACS, we examined the correlations of BPI levels with 14 clinical characteristics, 15 blood parameters, four inflammation biomarkers, and five CAG indexes in ACS patients. We adjusted p-values using the LD-adjusted Bonferroni correction to decrease the probability of Type I errors. The significance level was set as p < 0.005 after correction.
We found that plasma BPI levels positively correlated with the TIMI and GRACE scores (r = 0.176, p = 0.003; r = 0.320, p < 0.001) in patients with ACS, and this correlation was more significant in the whole cohort (r = 0.486, p < 0.001; r = 0.384, p < 0.001). After correction, the correlations of plasma BPI levels with the TIMI and GRACE scores were confirmed in patients with ACS (all p < 0.001) (Tables 3 and 4).
Table 3
Spearman correlation between BPI with clinical characteristics and inflammation Biomarkers
|
non-ACS (n = 111)
|
ACS (n = 256)
|
Whole Cohort (n = 367)
|
Variable
|
rs
|
p-value
|
rs
|
p-value
|
rs
|
p-value
|
Clinical characteristics
|
|
|
|
|
|
|
Age (years)
|
0.06
|
0.478
|
0.039
|
0.534
|
.140**
|
0.005
|
Gender (F=1, M=0)
|
-0.151
|
0.071
|
-0.005
|
0.941
|
-.177**
|
0
|
Heart rate(bpm)
|
-0.142
|
0.092
|
0.081
|
0.194
|
0.029
|
0.56
|
Systolic pressure(mmHg)
|
0.155
|
0.065
|
-0.074
|
0.237
|
0.029
|
0.56
|
BMI (kg/m2)
|
0.037
|
0.66
|
-0.132
|
0.061
|
-0.061
|
0.26
|
Hypertension
|
.188*
|
0.024
|
-0.07
|
0.262
|
0.034
|
0.496
|
Hyperlipidemia
|
-0.124
|
0.139
|
-0.033
|
0.598
|
-0.026
|
0.608
|
Diabetes mellitus
|
-0.106
|
0.208
|
-0.041
|
0.509
|
0.056
|
0.261
|
Smoking
|
0.027
|
0.747
|
0.08
|
0.201
|
.113*
|
0.024
|
Atrial fibrillation
|
0.049
|
0.557
|
0.106
|
0.091
|
0.093
|
0.062
|
Stroke
|
-0.12
|
0.15
|
0.004
|
0.945
|
0.073
|
0.145
|
Previous stenosis≥50%
|
.217**
|
0.009
|
-.305**
|
0
|
0.017
|
0.729
|
PreMI
|
0.134
|
0.11
|
-0.092
|
0.143
|
0.019
|
0.707
|
PrePCI
|
0.112
|
0.181
|
-.212**
|
0.001
|
0.025
|
0.62
|
TIMI score
|
.194*
|
0.02
|
.176**
|
0.003
|
.486**
|
0
|
Grace score
|
-0.135
|
0.108
|
.320**
|
0
|
.384**
|
0
|
Blood parameters
|
|
|
|
|
|
|
Blood neutrophils counts
|
-0.001
|
0.986
|
.266**
|
0.000
|
.316**
|
0
|
Blood leukocytes counts
|
-0.043
|
0.607
|
-0.1
|
0.12
|
-.111*
|
0.029
|
Neutrophils (%)
|
0.006
|
0.947
|
.263**
|
0
|
.290**
|
0
|
Blood platelets counts
|
-0.147
|
0.08
|
0.024
|
0.706
|
-0.056
|
0.268
|
Glucose(mmol/L)
|
-0.077
|
0.362
|
.138*
|
0.027
|
.135**
|
0.007
|
Cholesterol(mmol/L)
|
-0.06
|
0.477
|
0.116
|
0.075
|
0.004
|
0.944
|
Triglycerides(mmol/L)
|
0.061
|
0.473
|
-0.084
|
0.2
|
0.004
|
0.937
|
HDL (mmol/L)
|
0.044
|
0.603
|
-0.002
|
0.971
|
-.114*
|
0.027
|
LDL (mmol/L)
|
-0.054
|
0.524
|
0.127
|
0.051
|
0.006
|
0.907
|
Apolipoprotein A(mmol/L)
|
0.03
|
0.726
|
-0.018
|
0.78
|
-0.097
|
0.06
|
Apolipoprotein B(mmol/L)
|
-0.051
|
0.547
|
.137*
|
0.036
|
0.01
|
0.843
|
LP (a)(mmol/L)
|
.293**
|
0.002
|
-0.049
|
0.517
|
.117*
|
0.048
|
CK-MB (IU/L)
|
-0.021
|
0.829
|
.208**
|
0.002
|
.268**
|
0
|
Creatinine(µmol/L)
|
.182*
|
0.029
|
-0.094
|
0.136
|
0.092
|
0.065
|
Uric acid(µmol/L)
|
0.119
|
0.158
|
0.021
|
0.742
|
0.058
|
0.248
|
New biomarkers
|
|
|
|
|
|
|
Hs-CRP (pg/mL)
|
.700**
|
0
|
.554**
|
0.000
|
.746**
|
0
|
IL-1β(pg/mL)
|
.638**
|
0
|
.512**
|
0.000
|
.741**
|
0
|
MPO-DNA (ng/mL)
|
.403**
|
0
|
.452**
|
0.000
|
.611**
|
0
|
S100A8/A9 (ng/mL)
|
.211*
|
0.011
|
.434**
|
0.000
|
.529**
|
0
|
Coronary angiography
|
|
|
|
|
|
|
Number of diseased vessels
|
.665**
|
0
|
0.047
|
0.450
|
.489**
|
0
|
Calcified lesions
|
0.122
|
0.144
|
0.048
|
0.440
|
.128*
|
0.011
|
Chronic total occlusion
|
.258**
|
0.002
|
0.111
|
0.077
|
.264**
|
0
|
In-stent restenosis
|
.305**
|
0
|
-.173**
|
0.005
|
0.043
|
0.397
|
Total number of stents
|
0.111
|
0.184
|
-0.059
|
0.347
|
.277**
|
0
|
Gensini score
|
.701**
|
0
|
.263**
|
0.000
|
.605**
|
0
|
ACS, acute coronary syndrome. HDL, high density lipoprotein. LDL, low density lipoprotein.
|
CK-MB, MB isoform of creatine kinase. BMI, body mass index
|
BPI, bactericidal/permeability increasing protein
|
Hs-CRP, high sensitivity C-reactive protein
|
IL-1β, interleukin-1 β
|
** Correlation was statistically significant at 0.01 level (Two-tailed).
|
* Correlation was statistically significant at 0.05 level (Two-tailed).
|
Table 4
Unary linear regression of BPI
Index
|
B
|
S.E.
|
Beta
|
T
|
p
|
Hs-CRP (pg/mL) *
|
0.001
|
0
|
0.778
|
24.744
|
0
|
IL-1β (pg/mL) *
|
0.009
|
0
|
0.767
|
23.86
|
0
|
MPO-DNA (ng/mL) *
|
0.032
|
0.002
|
0.627
|
16.046
|
0
|
S100A8/A9 (ng/mL) *
|
1.264
|
0.098
|
0.543
|
12.893
|
0
|
Neutrophils(*10^9/L) *
|
3.392
|
0.459
|
0.353
|
7.385
|
0
|
Platelets(*10^9/L)
|
-0.008
|
0.016
|
-0.024
|
-0.476
|
0.634
|
Glucose(mmol/L) *
|
1.807
|
0.399
|
0.222
|
4.528
|
0
|
LP (a)(mmol/L)
|
0.007
|
0.004
|
0.113
|
1.906
|
0.058
|
Previous coronary artery disease≥50%
|
0.069
|
2.449
|
0.001
|
0.028
|
0.978
|
In-stent restenosis
|
3.663
|
5.615
|
0.033
|
0.652
|
0.515
|
TIMI score*
|
6.826
|
0.638
|
0.473
|
10.703
|
0
|
GRACE score*
|
0.276
|
0.03
|
0.424
|
9.342
|
0
|
Gensini score*
|
0.293
|
0.024
|
0.53
|
12.459
|
0
|
BPI, bactericidal/permeability increasing protein
|
Hs-CRP, high sensitivity C-reactive protein
|
IL-1β, interleukin-1 β
|
* p < 0.005
|
No significant correlations were found between plasma BPI levels and blood platelet counts, although recent RNA-seq data analysis reported the upregulation of BPI in the platelets of patients with STEMI/NSTEMI [42]. Plasma BPI levels positively correlated with blood neutrophil counts (r = 0.266, p < 0.001) in patients with ACS, and this correlation was more significant in the whole cohort (r = 0.316, p < 0.001). After correction, the correlations between plasma BPI levels and blood neutrophil counts were confirmed in patients with ACS (p < 0.001) (Tables 3 and 4, Figure 2).
In addition, we found that plasma BPI levels positively correlated with glucose levels (r = 0.138, p = 0.0027) in patients with ACS, and this correlation was also significant in the whole cohort (r = 0.135, p = 0.007). After correction, the correlations between plasma BPI levels and glucose levels were confirmed in patients with ACS (p < 0.001) (Tables 3 and 4).
We next examined the correlations of plasma BPI levels with the levels of hs-CRP, IL-1β, MPO-DNA, and S100A8/A9. Plasma BPI levels positively correlated with the levels of hs-CRP, IL-1β, MPO-DNA, and S100A8/A9 (r = 0.746; r = 0.741; r = 0.611; r = 0.529, all p < 0.001) in patients with ACS (Table 3). To identify factors independently associated with BPI, we performed linear regression analysis of plasma BPI levels with the concentrations of hs-CRP, IL-1β, MPO-DNA, and S100A8/A9 using Spearman’s correlation analysis. The p-values were corrected using the LD-adjusted Bonferroni correction. After correction, the correlations of BPI levels with the concentrations of hs-CRP, IL-1β, MPO-DNA, and S100A8/A9 persisted in patients with ACS (all p < 0.001). These results indicate that plasma BPI levels positively correlate with the concentrations of hs-CRP, IL-1β, MPO-DNA, and S100A8/A9 (Tables 3 and 4, Figure 3).
Correlation Of Plasma Bpi Level With Cag Results
We further investigated the correlations of BPI levels with CAG results, including “the number of diseased coronary arteries”, “calcified lesions, chronic total occlusion”, “in-stent restenosis”, and “total number of stents in coronary”. We found that plasma BPI levels positively and significantly correlated with “the number of diseased coronary arteries”, “calcified lesions, chronic total occlusion”, and “total number of stents in coronary” in the whole cohort (r = 0.489, p < 0.001; r = 0.128, p = 0.011; r = 0.264, p < 0.001; r = 0.277, p < 0.001), but not in patients with ACS. However, after LD-adjusted Bonferroni correction, the correlations of plasma BPI levels with the above indexes were not significant (Tables 3 and 4, Figure 4).
The severity of coronary atherosclerosis was assessed using the Gensini scoring system based on the CAG results. The Gensini scoring system is a well-recognized and widely used system that evaluates the severity of coronary atherosclerosis in the clinic [38, 43, 44]. We also evaluated the correlation between BPI levels and the Gensini score and found that higher plasma BPI levels were associated with higher Gensini scores in patients with ACS (r = 0.263, p < 0.001), as well as in the whole cohort (r = 0.605, p < 0.001) (Table 3). After correction, the correlation between plasma BPI levels and the Gensini score was confirmed in patients with ACS (p < 0.001) (Tables 3 and 4, Figure 4).
ROC analysis of the diagnostic efficacy of plasma BPI levels for ACS and MI
ROC curve analysis revealed that the optimal cut-off of plasma BPI levels for ACS was 29.01 ng/ml. The ROC curves for BPI, hs-CRP, IL-1β, MPO-DNA, S100A8/A9, and neutrophils are compared in Figures 5 and 6. We found that BPI, hs-CRP, IL-1β, MPO-DNA, S100A8/A9, and neutrophils all had diagnostic efficacy for ACS, with area under the curve (AUC) values of 0.93 (0.90 – 0.95), 0.87 (0.84 – 0.91), 0.87 (0.84 – 0.91), 0.81 (0.76 – 0.85), 0.76 (0.71 – 0.81), and 0.68 (0.62 – 0.73), respectively. The pairwise comparison of ROC curves using the Z-Test showed that the diagnostic efficacy of BPI levels for ACS was significantly different from that of hs-CRP, IL-1β, MPO-DNA, S100A8/A9, and neutrophils (BPI vs. hs-CRP: z = 2.856, p = 0.0043; BPI vs. IL-1β: z = 3.241, p = 0.0012; BPI vs. MPO-DNA: z = 5.316, p < 0.0001; BPI vs. S100A8/A9: z = 6.397, p < 0.0001; BPI vs. neutrophils: z = 8.186, p < 0.0001).
Using the same method, we found that the optimal cut-off of plasma BPI levels for MI was 38.71 ng/ml. The ROC curves for BPI, CK-MB, and cardiac troponin I (TnI) are compared in Figure 7. ROC curve analysis showed that BPI, CK-MB, and TnI all demonstrated diagnostic efficacy for MI, with AUC values of 0.88 (0.84 – 0.93), 0.71 (0.64 – 0.79), and 0.83 (0.78 – 0.89), respectively. Using the Z-Test, the diagnostic efficacy of BPI for MI was significantly different from that of CK-MB (BPI vs. CK-MB: z = 3.896, p = 0.0001), but no significant difference was observed between BPI and TnI (BPI vs. TnI: z = 1.448, p = 0.1475). The above findings indicate that the diagnostic value of BPI for MI is not inferior to that of TnI, and may be superior to that of CK-MB.