The serum levels of lipids profile (LDL, HDL, TG, and cholesterol), HS-CRP, NT-proBNP, FBS, FABP4, and S100A12
The mean serum concentrations of FABP4, S100A12, NT-proBNP, HS-CRP, and HDLin three groups are given in Table 2.
Table 2 The mean FABP4, S100A12, NT-proBNP, HS-CRP, and HDL
Variables
|
New cases (n=30)
|
Under-treatment (n=30)
|
Control (n=30)
|
P -value
|
FABP4(ng/ml)
|
4.62 ± 0.61
|
3.93 ± 0.87
|
3.30 ± 1.02
|
< 0.001
|
S100A12(pg/ml)
|
133.61 ± 23.60
|
114.87 ± 32.99
|
107.78 ± 37.66
|
0.005
|
NT-proBNP (Pg/ml)
|
67.61 ± 12.47
|
61.43 ± 11.99
|
59.60 ± 10.69
|
0.016
|
HS-CRP (mg/L)
|
7.35 ± 6.82
|
3.33 ± 1.95
|
2.23 ± 0.62
|
< 0.001
|
SCORE1.5
|
11.53 ± 12.19
|
8.83 ± 6.77
|
6.13 ± 6.60
|
0.078
|
FRS
|
9.96 ± 11.02
|
7.20 ± 6.16
|
4.71 ± 6.07
|
0.029
|
HDL (mg/dl)
|
42.73 ± 10.67
|
57.86 ± 13.97
|
44.30 ± 8.82
|
< 0.001
|
Data are Mean ± SEM; FABP4: Fatty acid binding protein 4, NT-proBNP: N-terminal pro–B-type natriuretic peptide, HS-CRP: High sensitivity C-reactive protein, HDL: High Density Lipoprotein
The comparison of lipids profile, HS-CRP, NT-proBNP, FBS, FABP4, and S100A12 in patients (new case + under-treatment) and control group
The serum levels of FABP4, S100A12, HDL, NT-proBNP, and HS-CRP were substantially different between the RA patients (new cases and under-treatment) and healthy individuals (P < 0.001, P = 0.005, P < 0.001, P = 0.016, P < 0.001, respectively). Still, the serum concentration of TG, cholesterol, LDL, FBS, BPD (diastolic blood pressure), BPS (systolic blood pressure) and BMI were not significantly different between the three groups of the study population (P = 0.241, P = 0.427, P = 0.105, P = 0.093, P = 0.191, P = 0.593, P = 0.223 respectively). Among CVD risk calculators, FRS was different between the RA patients and healthy subjects While SCORE was not different between the three groups (P = 0.029 and P = 0.078) (Figure 1).
Fig.1 Comparing the plasma levels of FABP4, S100A12, NT-proBNP, and HS-CRP among three groups
Fig.1 caption
The plasma concentration of FABP4, S100A12, and NT-proBNP was quantified by the sandwich ELISA method. Also, the plasma levels of HS-CRP were read using the ADVIA 1800 Clinical Chemistry System, which was quantified by the Immunoturbidimetric assay. a) Comparing the plasma level of FABP4 among the three groups, which significantly was higher in the newly diagnosed and under-treatment RA patients compared to healthy subjects (P <0.001 and P = 0.008, respectively). However, there was a remarkable difference between the new case and patient groups (P = 0.009). b) The graph showed a significant rise of S100A12 in the new case compared to control groups (P =0.001), though there was not a remarkable difference between the under-treatment RA patients compared to healthy subjects (P =0.322). c) The plasma level of NT-proBNP was substantially higher in newly diagnosed compared to control groups (P <0.01), Also there was not a remarkable difference between the under-treatment patients and control groups (P =0.246). d)The Plasma level of HS-CRP was significantly higher in the newly diagnosed and under-treatment RA patients compared to healthy subjects (P <0.001 and P = 0.013, respectively). However, there was a remarkable difference between the new case and under-treatment RA patient groups (P = 0.020).
Assessment of correlation between variables in patients group (new case + under-treatment)
The correlation between the plasma concentration of FABP4 and S100A12 with BMI, LDL/HDL, TG, Cholesterol, FBS, BPS, BPD, NT-proBNP, HS-CRP, DAS-28 and CVD risk calculator( FRS and SCORE) in the patients group (new case + under-treatment) was shown in Table 3.
Table 3 Correlation between the plasma level of FABP4 and S100A12 with clinical and laboratory parameters
RA patients
|
FABP4
|
S00A12
|
BMI
|
TG
|
Chol
|
FBS
|
HDL
|
LDL
|
BPS
|
BPD
|
NT-proBNP
|
HS-CRP
|
SCORE
|
FRS
|
DAS-28
|
FABP4
|
r =
1
|
r = .585
|
r = .056
|
r = .055
|
r = .041
|
r = .033
|
r = -.224
|
r = -.098
|
r = .0366
|
r = .077
|
r = .493
|
r = .399
|
r = .277
|
r = .0297
|
r = .285
|
|
|
P <.001
|
p = .674
|
p = .675
|
p = .754
|
p = .801
|
p = .085
|
p = .454
|
p = .004
|
p = .559
|
p <.001
|
p = .002
|
p = .032
|
p = .021
|
p = .027
|
S100A12
|
r = .585
|
r =
1
|
r = .127
|
r = .041
|
r = .122
|
r = -.032
|
r = -.183
|
r = -.190
|
r = -.026
|
r = -.220
|
r = .445
|
r = .069
|
r = .017
|
r =- .004
|
r = .213
|
|
p <.001
|
|
p = .333
|
p = .753
|
p = .353
|
p = .809
|
p = .161
|
p = .147
|
p = .841
|
p = .091
|
p <.001
|
p = .599
|
p = .900
|
p = .975
|
p = .102
|
FABP4: Fatty acid binding protein 4, BMI: Body Mass Index, TG: triglyceride, Chol: Cholesterol, FBS: Fasting Blood Sugar, HDL: High Density Lipoprotein, LDL: Low Density Lipoprotein, BPS: Systolic blood pressure, BPD: Diastolic Blood Pressure, NT-proBNP: N-terminal pro–B-type natriuretic peptide, HS-CRP: High sensitivity C-reactive protein, SCORE: Systematic Coronary Risk Evaluation, FRS: Framingham Risk Score, DAS-28: Disease activity score-28
In the patient group(newly diagnosed and under-treatment), There was a significantly positive correlation between the plasma concentration of FABP4 with S100A12 (r =0.585, P < 0.001), FABP4 with BPS (r =0.366, P = 0.004), FABP4 with NT-proBNP (r =0.493, P < 0.001), FABP4 with HS-CRP (r =0.399, P = 0.002), FABP4 with SCORE (r =0.277, P = 0.032), FABP4 with FRS (r =0.297, P = 0.021) and FABP4 with DAS-28 (r =0.285, P = 0.027), though was a negative correlation between FABP4 with HDL (r =-0.224, P = 0.085) and LDL (r =-0.098, P = 0.454). As well as there was also a significantly positive correlation between the serum levels of S100A12 with NT-proBNP (r =0.445, P < 0.001) and a negative correlation between S100A12 with HDL (r =-0.183, P = 0.161), S100A12 with LDL (r =-0.190, P = 0.147), S100A12 with BPS (r =-0.026, P = 0.841), S100A12 with BPD(r =-0.220, P = 0.091) and S100A12 with FRS (r =-0.004, P = 0.975). Also, in the patient groups, we did not find a significant correlation between BMI, TG, Cholesterol, and FBS with FABP4 and S100A12 (Figure 2).
Fig.2 Correlation between plasma levels of FABP4 and S100A12 with different variables in the patient groups
Fig.2 caption
Correlation analysis was done using Spearman and Pearson correlations. a)In the patient groups, FABP4 plasma concentration was positively a) S100A12 (r =0.585, P < 0.001), b) BPS (r =0.366, P = 0.004), c) NT-proBNP (r =0.493, P < 0.001), d) HS-CRP (r =0.399, P = 0.002), E) SCORE (r =0.277, P = 0.032), F) FRS (r =0.297, P = 0.021) and G) DAS-28 (r =0.285, P = 0.027). H) There was a positive correlation between the S100A12 with NT-proBNP (r =0.445, P < 0.001).
Analysis of FABP4 and S100A12 According to CVD Risk Calculators of FRS and SCORE
We found in newly diagnosed patients significant differences between FABP4 with FRS (P = 0.008), FABP4 with SCORE (P = 0.024), and in patient groups was a positive correlation between FABP4 with FRS (P = 0.021), FABP4 with SCORE (P = 0.032), which is mentioned in Table 4.
Table 4 Analysis of FABP4 and S100A12 calculated in the Newly Diagnosed Patients, and Under-treatment Patients According to the CVD Risk Calculator of the FRS and SCORE, which into Low, Moderate, and High-risk groups for FRS, and Low-moderate, high, and high-risk groups for SCORE are classified
|
FRS
|
SCORE
|
New cases (n=30)
Under-treatment (n=30)
Patients(n=60)
(New cases+ Under-treatment)
|
FABP4
S100A12
FABP4
S100A12
FABP4
S100A12
|
P = 0.008
P = 0.517
P = 0.647
P = 0.971
P = 0.021
P = 0.975
|
P = 0.024
P = 0.618
P = 0.474
P = 0.637
P = 0.032
P = 0.900
|
FRS classification: (Low risk: FRS < 10%, moderate risk: FRS 10–20%, high risk: FRS > 20%), SCORE classification: (under age 50: Lowmoderate risk: SCORE < 2.5%, high risk: SCORE 2.5–7.5%, very high risk: SCORE > 7.5%), (over age 50: Low-moderate risk: SCORE < 5%, high risk: SCORE 5–10%, very high risk: SCORE > 10%)